ENTERING CANADIAN LONG-TERM CARE WITH OBESITY:
EXPLORING INITIAL ASSESSMENT DATA
by
Alishia Lindsay
B.A, University of Northern British Columbia, 2015

THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
HEALTH SCIENCES

UNIVERSITY OF NORTHERN BRITISH COLUMBIA
July 2023
© Alishia Lindsay, 2023

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Abstract
The Canadian population is aging, and rates of obesity are also on the rise. These
demographic changes have implications for the long-term care (LTC) system in Canada that
need to be better understood, yet little is known about the population with obesity in Canadian
LTC. In this thesis, an exploratory analysis of residents newly entering LTC between 2010 and
2020 is provided. Cross-tabulations and chi-squared statistical testing (p≤0.001) were employed
to analyze retroactive, consecutive cross-sectional initial assessment data (N=350,348) from the
Canadian Institute for Health Information’s (CIHI) Community Care Reporting System (CCRS)
to explore the levels of obesity, demographic characteristics (age, sex, primary language, rural or
urban previous residency), rates of health conditions, and independence and assistance levels of
activities of daily living (ADLs). Over the full study period, the rate of obesity for the population
entering LTC was 19%, and 7% entered with at least class II obesity (≥35 kg/m2). Rates of
obesity and BMI obesity categories tended to increase incrementally over the course of the study
period. Those entering LTC with obesity were more likely to be younger, female, English/French
speaking, and arriving from rural areas. Individuals with obesity had lower rates of dementia and
higher levels of independence when performing ADLs. They also exhibited higher rates of
diabetes and a greater need for two+ person assistance for ADLs. This thesis begins to fill in the
gap in our understanding of the population with obesity in LTC, providing a broad picture of the
heterogeneous nature of the population, including important differences in health and ADL
profiles across the three obesity BMI categories (i.e., classes I-III).

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Table of Contents
Abstract ........................................................................................................................................... ii
Table of Contents ........................................................................................................................... iii
List of Tables ................................................................................................................................. vi
List of Figures ............................................................................................................................... vii
Acknowledgements ........................................................................................................................ ix
Chapter One: Introduction .............................................................................................................. 1
Research Objective and Questions...................................................................................... 2
Overview of the Thesis ....................................................................................................... 3
Chapter Two: Literature Review .................................................................................................... 5
Long-Term Care in Canada ................................................................................................ 5
Obesity .............................................................................................................................. 10
Definition .............................................................................................................. 10
Body Mass Index .................................................................................................. 12
Adjustments of BMI Health Risks ........................................................................ 15
Obesity Prevalence............................................................................................................ 19
Obesity in Long-Term Care (LTC) ................................................................................... 20
Age, Obesity and LTC .......................................................................................... 27
Health Conditions, Obesity and LTC.................................................................... 28
Activities of Daily Living, Obesity and LTC ....................................................... 30
Equity Considerations ....................................................................................................... 31
Weight Bias ........................................................................................................... 32
Chapter Three: Methods ............................................................................................................... 34
Data Sources ..................................................................................................................... 34
Ethics................................................................................................................................. 36
Research Sample ............................................................................................................... 36
Research Design................................................................................................................ 36
Initial Data and Clean-up ...................................................................................... 37
Facility Characteristics.......................................................................................... 39
Demographic Variables ........................................................................................ 40
Morbidity and Multiple Morbidities ..................................................................... 41
Activities of Daily Living - Independence............................................................ 42
Statistical Tests ................................................................................................................. 43
Chapter Four: Results ................................................................................................................... 45

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Assessment Frequencies ................................................................................................... 45
Profile of Persons Newly Residing in a LTCF (2010-2020) ............................................ 47
Incidence ........................................................................................................................... 47
Frequency of Obesity ............................................................................................ 48
Incidence of Obesity ............................................................................................. 49
Provincial Incidence of Obesity ............................................................................ 50
Incidence of Persons Newly Residing in a Long-term Care Facility Weighing 115
Kg or More ............................................................................................................ 52
Summary of Incidence of Obesity ........................................................................ 53
Demographic Characteristics ............................................................................................ 54
Age Distribution.................................................................................................... 54
Age Groups; In-Community and Entering Long-term Care ................................. 56
Sex......................................................................................................................... 59
Language ............................................................................................................... 60
Location of Last Residence ................................................................................... 61
Location of Last Residence by Province/Territory ............................................... 62
Summary of Demographic Profile ........................................................................ 64
Health Status ..................................................................................................................... 64
Chronic Health Conditions ................................................................................... 64
Multiple Chronic Health Conditions ..................................................................... 67
Multi-Morbidities Over Time ............................................................................... 68
Dyads of Chronic Conditions................................................................................ 69
Summary of Chronic Health Conditions............................................................... 72
Activities of Daily Living (ADLs) .................................................................................... 72
Two+ Person Assistance ....................................................................................... 73
Self Performance of Activities of Daily Living (ADLs) ...................................... 76
Proportional Ratios ............................................................................................... 76
ADL Independence as Stratified by Dementia and Obesity ................................. 77
ADL Independence Level of Reference Group (Normal BMI) ............................ 80
Summary of Self Performance of Activities of Daily Living (ADLs).................. 85
Summary of Results .............................................................................................. 86
Chapter Five: Discussion .............................................................................................................. 88
What Do We Know About Persons Newly Residing In LTCFs with Obesity? ............... 89
Understanding the Care Needs of Persons Newly Residing In LTCFs with Obesity ....... 94
The Limitations and Usefulness of BMI Categories Amongst Persons Newly Residing In
a LTCF ............................................................................................................................ 100
The Impacts of the COVID-19 Pandemic ....................................................................... 101
A Priority Population ...................................................................................................... 102
Chapter Six: Conclusion and Recommendations ........................................................................ 104

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Limitations ...................................................................................................................... 104
Geography ........................................................................................................... 104
Assessments ........................................................................................................ 105
Missing Data ....................................................................................................... 107
Selection Bias...................................................................................................... 108
The Population Newly Admitted to LTC with Obesity .................................................. 109
Implications..................................................................................................................... 110
Knowledge Dissemination .............................................................................................. 111
Recommendations for Future Actions and Research ...................................................... 111
References ................................................................................................................................... 113
Appendices .................................................................................................................................. 139

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List of Tables
Table 1 Number of Participating Long-Term Care Facilities by Fiscal Year, 2016/17-2020/21 . 40
Table 2 Frequencies of Body Mass Index (BMI) Categories of Persons Newly Residing in a
Long-term Care Facility by Geographical Group (N=350,348), 2010-2020 .................. 50
Table 3 Rates of Body Mass Index (BMI) Categories by Sex of Persons Newly Residing in a
Long-term Care Facility (N=348,970), 2010-2020 ......................................................... 59
Table 4 Location of Last Residence of Persons Newly Residing in a Long-term Care Facility by
Province (N=340,358), 2010-2020 .................................................................................. 63
Table 5 Chronic Health Conditions of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020 ................................................................................................. 66
Table 6 Top Five Dyads of Chronic Health Conditions of Persons Newly Residing in a Longterm Care Facility, 2010-2020 (n=350,348), and In-Community Adults Over 65 for the
Year 2008 (n=3,132) ....................................................................................................... 71
Table 7 Two+ Person Assistance Required by Person Newly Residing in a Long-term Care
Facility (N=350,348), 2010-2020 .................................................................................... 75
Table 8 Stratified Frequencies of Dementia and Body Mass Index for Person Newly Residing in
a Long-term Care Facility (N=350,348), 2010-2020 ...................................................... 76
Table 9 Independence of Activities of Daily Living (ADLs) for Person Newly Residing in a
Long-term Care Facility (N=350,348), 2010-2020 ......................................................... 78
Table 10 Independence of Activities of Daily Living, for Person Newly Residing in a Long-term
Care Facility with a Normal Body Mass Index (N=146,224), 2010-2020 ...................... 80

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List of Figures
Figure 1 Distribution of Body Mass Index (BMI) of All Persons Newly Residing in a Long-term
Care Facility (N=356,890) and Persons Newly Residing in a Long-term Care Facility
Entering from Residential Care (n=87,414), 2010-2020 ................................................. 38
Figure 2 Valid and Missing Body Mass Index (BMI) by Weight Category of Persons Newly
Residing in a Long-term Care Facility (N=350,348), 2010-2020 ................................... 39
Figure 3 Annual Frequency of First Initial Assessment of Persons Newly Residing in a Longterm Care Facility (N=350,348), 2010-2020 ................................................................... 46
Figure 4 Annual Provincial/ Territorial Frequencies of First Initial Assessment of Persons Newly
Residing in a Long-term Care Facility (N=350,348), 2010-2020 ................................... 46
Figure 5 Persons Newly Residing in a Long-term Care Facility by Body Mass Index (BMI)
Category (N=350,348), 2010-2020 ................................................................................. 48
Figure 6 Annual Rates of Body Mass Index (BMI) Amongst Persons Newly Residing in a Longterm Care Facility (N=350,348), 2010-2020 ................................................................... 49
Figure 7 Annual Rates of Obesity Amongst Persons Newly Residing in a Long-term Care
Facility by Geographical Group (N=350,348), 2010-2020 ............................................. 51
Figure 8 Trend Lines of Obese Classes Amongst Persons Newly Residing in a Long-term Care
Facility by Geographical Group (N=350,348), 2010-2020 ............................................. 52
Figure 9 Annual Rates of Individuals at Risk of Needing Bariatric Equipment Amongst Persons
Newly Residing in a Long-term Care Facility (N=350,348), 2010-2020 ....................... 53
Figure 10 Age Distribution of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020 ................................................................................................. 55

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Figure 11 Comparison of Rates of Obesity for Persons Aged 50 and Older Newly Residing in a
Long-term Care Facility (n=346,283) and Adults Aged 50 years or Older Residing in
Community Settings (n=288,547), 2009-2018 ................................................................ 57
Figure 12 Rates of Obesity Amongst Persons Aged 60+ Newly Residing a in Long-term Care
Facility (n=336,762) and Older Adults Aged 60+ in Community Settings, 2010-2020
(n=192,641), 2010-2018 .................................................................................................. 58
Figure 13 Sex Distribution of Persons Newly Residing in a Long-term Care Facility
(N=348,970), 2010-2020 ................................................................................................. 60
Figure 14 Primary Language Distribution of Persons Newly Residing in a Long-term Care
Facility (N=350,348), 2010-2020 .................................................................................... 61
Figure 15 Location of Last Residence of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020 ................................................................................................. 62
Figure 16 Multiple Chronic Health Conditions of Persons Newly Residing in a Long-term Care
Facility (N=350,348), 2010-2020 .................................................................................... 68
Figure 17 Proportional Ratios of Obesity Status for Independence in Activities of Daily Living of
Persons Newly Residing in a Long-term Care Facility (N=350,348), 2010-2020 .......... 79
Figure 18 Proportional Ratios of Body Mass Index Categories of Independence of Activities of
Daily Living for Persons Newly Residing in a Long-term Care Facility (N=350,348),
2010-2020 ........................................................................................................................ 83

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Acknowledgements
I would like to first express my deepest gratitude to my supervisor and chair of my
committee Neil Hanlon, for his patience and feedback, and for giving me the opportunity to

manage the present study and for providing me with invaluable guidance throughout the
research. I am also thankful to my defense committee members, Drs. Shannon Freeman and
Davina Banner-Lukaris, who generously provided knowledge and expertise, and to Dr. Martha
Macleod for their valuable feedback as my external examiner.

I am grateful to have received funding through the Yvette and Dollard Bock Health
Research Award, and from the Old Age Pensioners Society in 2020. Such funding made it
possible for me to pursue my research.

Lastly, I am also grateful for my supportive husband, Chris Reeves, with whom I have
two beautiful and amazing children, including one born in the middle of the completion of this
thesis. His unwavering belief in me has been monumental in helping me reach this stage of my
academic career.

I dedicate this thesis to all those who have family, or themselves are facing challenges in
accessing healthcare and to those working tirelessly and selfless in healthcare making differences
everyday in the worlds of those families.

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Chapter One: Introduction
The Canadian healthcare system is designed to have more specialized and resource
intensive care concentrated in larger centres. A member of my family, who happens to be
bariatric, experienced a health emergency that required transportation to a hospital in a larger
center. Their access to necessary care was delayed for several days. We were told that a major
reason for this delay was that there was, at the time, only one aircraft capable of transporting a
bariatric patient in the province. Luckily for this family member, they were able to wait for the
aircraft to finish transporting another patient, re-fuel, and reset pilot hours before being
transported.
This experience initiated my curiosity and concern about how well-equipped our
healthcare system is for providing appropriate and quality care to persons with higher body mass
index (BMI). The presence of weight bias in society and the healthcare system added to the
feeling of the importance of this topic. At the same time, I was also aware of the reports
signalling concern for the aging Canadian population and what that would mean for the Canadian
healthcare system, including long-term care (LTC). Ultimately, the idea to study persons with
obesity newly residing in Canadian a long-term care facility (LTCF) enabled me to combine
these two interests.
My thesis journey began in 2019, and the importance of understanding obesity and its
effects on care in long-term care facilities (LTCFs) was further emphasized by the dramatic
impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19)
pandemic that began the following year. The effects of the pandemic on Canadian LTC brought
with it calls for reform, highlighting the need to understand the staffing and resource demand of

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all persons residing in LTCFs (Canadian Institute for Health Information, 2020b; Ho, 2020; Stall
et al., 2021).
By offering an evidence-based understanding of the group of older adults with obesity,
this thesis is intended to begin filling gaps in knowledge surrounding this population. It also
intends to help dispel weight-based stereotypes, stigma, and barriers for those with obesity.
Additionally, the thesis focuses on the population entering LTCFs specifically (as opposed to
persons already residing in a LTCF), providing information for LTC and for in-community and
alternative care structures. Canadian Institute for Health Information's (CIHI) initial assessment
data collected in select LTCFs between Jan-1-2010 through Dec-31-2020 is utilized to explore
the incidence of those entering LTC with obesity, their demographics, and their care needs.
Research Objective and Questions
This thesis aims to learn more about changes in the rates of obesity seen in the population
entering LTC and to prepare a profile of the health and care needs of this population segment.
The following research questions were developed to achieve this objective:
1) What is the rate of obesity among those persons newly residing in a LTCF, and has this
rate increased over time?
2) What are the demographic and health characteristics of those entering LTC with obesity,
and how do these characteristics compare to newly admitted persons residing in a LTCF
who are not considered obese?
3) What are the care needs of those entering LTC with obesity, and how do these needs
compare to newly admitted persons residing in a LTCF who are not considered obese?
4) What are the differences seen in these three questions when applied to six BMI categories
rather than just obese and non-obese?

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Overview of the Thesis
In chapter two, I offer a review of the literature that informs this research. The chapter
begins with a brief overview of LTC in Canada, followed by a discussion of obesity, its
definitions, relation to body mass index (BMI), and possible adjustments to the health risks
associated with obesity. After that, discussion of the prevalence of obesity in the general
population and long-term care is offered. I then provide a discussion of factors known to lead to
an increased risk of needing LTC, the presence of obesity-based barriers, and the ways in which
having obesity interacts with age, health conditions, and activities of daily living (ADLs) in LTC
settings. Finally, I consider literature about equity in healthcare, emphasising the barriers and
biases faced by individuals with obesity and the rationalization for using first-person language
when conducting obesity-based research.
Chapter three outlines the data and methods used to conduct my analysis. First, the
research sample is defined, and the research design is outlined. This includes a detailed
discussion of the CCRS dataset from CIHI generally and the particular variables included in the
dataset. This is followed by a discussion of the quantitative methods and statistical tests
employed, including a description of an index created to track multi-morbidities and the use of
proportional ratios to visually represent differences in ADL levels across the BMI spectrum.
The findings of this work are presented in chapter four. These findings are organized into
three sections. The first section provides estimates of the numbers of persons newly residing in a
LTCF by BMI category. The second section offers a profile of the demographic and health
characteristics of the persons newly residing in a LTCF by BMI category. The third section
examines ADLs by BMI category, with levels stratified by illness (dementia, non-dementia).

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In chapter five, I offer a discussion of the major findings of the research. Particular
attention is paid here to how my research findings relate to relevant literature in Canadian and
international study contexts. I begin with a summarization of the results of the study and the
critical highlights of the profile created. This discussion then expands to the care needs of
individuals with obesity in LTCFs specific to the different rates of illnesses (i.e., diabetes and
dementia), and considers the need for nuance in the management of obesity and diabetes in
LTCFs. Another key finding discussed is the usefulness of BMI threshold levels amongst an
older adult population and the suggestion to lower the risks associated with low levels of obesity
for this population. There is then a brief section on the COVID-19 pandemic and its impact on
the data and the Canadian LTC sector. The chapter ends with a consideration of whether persons
with obesity in LTCFs should be considered a priority population for the purposes of ensuring
health equity.
In chapter six, I conclude the thesis by considering the limitations of my analysis, key
policy considerations, plans for knowledge dissemination, and suggestions for further study. The
limitations relate to the nature of the initial assessments, simplified geographical definitions, lack
of information about facility characteristics, and missing data. Key policy considerations call
attention to the unique care needs and resource implications of individuals with obesity in
LTCFs, noting especially the heterogeneity of the LTC population with obesity. Implications are
also described, focusing on the increase in obesity rates and the need to evaluate the Canadian
LTC sector’s ability to provide adequate care to those with higher obesity levels. I then outline
plans for knowledge dissemination to researchers, policy makers and practitioners. Lastly, I call
for more research on, and with, persons living with obesity in LTCFs.

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Chapter Two: Literature Review
Long-Term Care in Canada
Canada provides institutional care outside of hospitals through long-term care (LTC) and
its long-term care facilities (LTCFs), often called nursing homes, continuing care facilities, and
residential care homes (hereafter referred to simply as LTC or LTCFs). LTC is defined by Health
Canada (Government of Canada, 2004, sec. Long-term Facilities-based Care) as generally
providing "living accommodations for people who require on-site delivery of 24-hour, 7 days a
week supervised care, including professional health services, personal care, and services such as
meals, laundry, and housekeeping". LTCFs fall under the provincial jurisdiction of healthcare
provision and are not publicly insured under the Canada Health Act (Government of Canada,
2004). Canadian LTCFs offer a range of services and ownership types, with 46% of Canadian
facilities publicly owned, 29% privately owned and for-profit, 23% privately owned and not-forprofit, and 2% privately owned without a breakdown of profit or non-profit (Canadian Institute
for Health Information, 2021c). The distribution of privately and publicly owned LTCFs varies
widely across Canada, with, for example, 98% of Newfoundland and Labrador's 40 LTCFs
publicly owned compared to only 16% of Ontario's 627 LTCFs (Canadian Institute for Health
Information, 2021c).The Canadian long-term care sector was not purposefully developed but
evolved over time. Beginning with roots in the Elizabethan Poor Law of 1601 and alongside
religious orders, poorhouses were tasked with caring for those unable to care for themselves
(e.g., the poor, mentally ill, and older adults) (Estabrooks et al., 2020). In the early 20th century,
the gradual introduction of facilities tailored to an older adult population gave rise to more
modern institutional LTCFs (Estabrooks et al., 2020). In general, modern LTCFs are
institutionalized settings, with multiple people living communally in a facility staffed with

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various health and life care professionals, providing accommodation and care for older adults
unable to live in their own homes. While modern LTCFs provide services to people of a range of
ages, the large majority of persons residing in LTCFs continue to be older adults.
Approximately 53% of persons residing in Canadian LTCFs are over the age of 84, with
only 6.8% of the LTC population below the age of 65 (Canadian Institute for Health Information,
2022b). It is of interest to LTCFs that the Canadian population is undergoing a demographic shift
as baby boomers (those born between 1946 and 1964) reach a more advanced age. The number
of Canadians over the age of 80 in 2040 is expected to be more than double the 2020 population
numbers (from 1.7 million to 3.5 to 4 million), with 1.8 million over the age of 85 (Statistics
Canada, 2019). Concurrently, older adults will constitute a larger proportion of the population
than previous generations, for example, Canadians aged 50-70 accounted for 18% of the total
population in 1996, but this proportion grew to 24% of the population in 2016 (Statistics Canada,
1997, 2017b). After the doubling in population size, it is expected that the over-80 age group will
then only grow to around 4 or 5 million through to 2060 (Statistics Canada, 2019).
In 2016, there were approximately 246,000 persons residing in Canadian LTCFs
(Statistics Canada, 2017a). If the age-specific rates of demand in 2021 remains constant and the
projections reported above are correct, the LTC sector will need to accommodate 563,000 people
by 2040 as baby boomers reach the average age of a LTC resident (Statistics Canada, 2017a,
2019). This projected demand does not consider factors such as current unmet needs. In 2019, for
example, 98.7% of LTC beds in Ontario were utilized, with 34,834 people on the waitlist and an
average placement time of approximately 140 days, with wait times ranging from 52 days up to 5
years (Bueckert, 2021; Ontario Long Term Care Association, 2019). Additionally, by
encompassing a larger proportion of the population than previous generations, older-adult

7
healthcare services, including LTC and alternatives to LTC, will need to expand while relying
upon a relatively smaller available workforce and tax base (Eisen & Emes, 2022). Having a
better understanding about who is transitioning into LTC, and why, will better inform future
planning, policies, and funding for programs, including those that delay or prevent the need for
expensive institutional LTC while simultaneously preparing LTC for the increase in demand.
While seen as a more cost-effective option over more resource-intensive in-hospital care,
LTCFs are generally more expensive than in-community support and other alternatives (Kuluski,
Williams, Berta, et al., 2012). Remaining at home with in-community support is generally
preferred by older adults, especially after the COVID-19 pandemic (Leroux et al., 2021; Ontario
Long Term Care Association, 2015; Weeks et al., 2021). Alongside informal at-home care or
formal at-home community care programs, alternative care levels exist in assisted living
facilities, greenhouses, virtual villages, or niche retirement communities to name a few (Haber,
2016). Programs, such as rehabilitation/exercise programs, adult day care programs, and early
detection services support caregivers and assist in maintaining the physical and cognitive
functioning of older adults, especially those with dementia (Canadian Institute for Health
Information, 2023). Such home services, alternatives, and programs may help delay or prevent
entrance into LTC, and they can also encourage shorter LTC stays, allowing persons residing in
a LTCF to transition out of the LTCF; however, there are gaps in understanding availability and
eligibility for community-based care services (Freeman et al., 2017). Efforts to minimize LTC
through community care programs are hampered because these programs are traditionally
underserviced, and there is also an over-reliance and exploitation of unpaid informal and
predominantly female caregivers (Haber, 2016; Kuluski, Williams, Laporte, et al., 2012). Gaps
in formal care provision are especially prevalent in rural centres, often coupled with an

8
unfounded assumption that sufficient informal family, community and volunteer services are
standing by to substitute (Brassolotto et al., 2020).
The availability and accessibility of such programs are affected by social determinants of
health, such as barriers imposed by rural living (Camargo-Plazas et al., 2022; Morgan et al.,
2015). Individuals on waitlists for LTC in rural areas in Ontario tended to be less impaired than
their urban counterparts, reflecting somewhat the limited capacity for in-community programs in
rural areas (Kuluski, Williams, Laporte, et al., 2012). Recently, one in nine new persons residing
in a Canadian LTCF had the potential to have been cared for at home if in-community services
could have been available (Canadian Institute for Health Information, 2020a), and this number
rose to 50% of rural individuals on Ontarian waitlists (Kuluski, Williams, Berta, et al., 2012).
Alongside availability limitations, rural and smaller community programs face unique challenges
communities benefit from policies and practices that can be customized for a settings based
context (Brassolotto et al., 2020). Acknowledging and empowering alternatives and at-home care
programs, especially rural and remote home care programs, has the potential to reduce LTC
demand (Brassolotto et al., 2020; Canadian Home Care Association, 2006).
The effort to reduce LTC usage also affects the LTC system itself. When Ontario
changed its LTC admission policies to delay LTC entrance by increasing required care needs,
fewer people qualified for LTC resulting in individuals entering "older, frailer, and in need of
more medical and personal care than ever before" (Ontario Long Term Care Association, 2015,
p. 2). LTCFs in Ontario, therefore, saw a concentration of high-needs individuals within their
facilities, whereas before, there was a mix of needs, consequentially changing the role of LTC
without modernizing funding or staffing resources (Ontario Long Term Care Association, 2015).
Similar policies have been implemented in other areas, and the results of such policies in these

9
areas offer insights into what pragmatic success may look like; for example, at-home aging
policies in New York State resulted in a delay in seeking institutionalized care of only eight
months (Young et al., 2015). Ontario has implemented new policies in 2022, but how well the
new funding policies will account for concentrations of high-needs individuals remains to be
determined (Ontario Ministry of Long-Term Care, 2022).
The COVID-19 pandemic emerged in Canada in January 2020 and greatly affected the
Canadian health sector. LTCFs were heavily impacted as cases of COVID-19 in the Canadian
LTC population accounted for 3% of total COVID-19 cases in Canada and 45% of COVIDrelated deaths (Canadian Institute for Health Information, 2021b). The impacts of COVID-19
and responses to the COVID-19 pandemic were not even across LTCFs or provinces in Canada
(Cox et al., 2023; Khaketla et al., 2022; Liu et al., 2020; Patterson et al., 2023; Stall et al., 2020,
2021). Additionally, COVID-19 restrictions and implementation levels varied across regions and
between facilities, having far-reaching social, emotional, and health effects on persons residing
in Canadian LTCFs, families of those residing in LTCFs, and staff (Chamberlian et al., 2022;
Hung et al., 2022; K. Jones et al., 2022). The full effects of the COVID-19 pandemic on
Canadian LTCFs will continue to be a focus for researchers (Chen et al., 2023; Thompson et al.,
2020; Webber et al., 2022).
Addressing the current demand, and the projected increase, requires the adaptability of
both the LTC sector and community-based programs to increase capacity, minimize barriers, and
adapt to population needs. Persons residing in a LTCF and older adults in the community are not
a homogenous group, and various supports or services are needed to assist with delaying,
preventing, or shortening LTC stays. Individuals requiring LTC or support services are
vulnerable, with sub-populations facing different barriers to accessing health services (Canadian

10
Home Care Association, 2006). LTC populations which are under-researched include adults and
older adults with obesity, which will be discussed below.
Obesity
Definition
Obesity is a common metabolic/nutritional disease in which "an individual accumulates
abnormal or excessive fat for age and gender" (Venes, 2017, pp. 1670–1671). The individualistic
nature of the condition of obesity makes its legal definition challenging to ascertain, with debate
about whether obesity should be seen as a disability itself or as a disease that results in disability
(Mulrooney, 2019; Puhl & Heuer, 2009). Obesity is a complex, multifaceted phenomenon with
far-reaching individual and social components. It is important to acknowledge that obesity does
not necessarily equate to poorer health and is only one factor that contributes to a person's
overall health.
The use of language in research, publishing, and healthcare has implications for those
with obesity, and there has been a push to use the ubiquitous 'first-person' language such as
'person with obesity' or 'having obesity' rather than an 'obese person' or 'being obese.' The firstperson language of 'having obesity' is used to reposition the rhetoric from one conflating obesity
as permeating and defining one's identity to instead describing one as having a medical condition
called obesity with an acknowledgement of the complexities surrounding its cause (Mulrooney,
2019). The use of first-person language is not without its critics. An example of a condition
whose community does not prefer first-person language is the Autistic community because
Autism permeates a person’s identity, with every aspect of their existence seen through a lens of
Autism (the choice of language varies by individual as well here) (Porch, 2022, pp. xv–xvii).
With Autism as an example of an identity-permeating condition, the concern about obesity is

11
how far-reaching it is as a feature of one's identity. In the case of first-person language, its
purpose is to separate the characteristic of obesity from a person's identity. However, that very
act could be seen as implying an "inherent adverse judgement" and places obesity as a "defect"
or "burden" separating one from a "normal" form (Meadows & Daníelsdóttir, 2016, pp. 1–2).
The descriptors for the extent of obesity continue to evolve, with terms such as 'fat,' 'extreme
obesity,' 'morbid obesity,' 'severe obesity,' and 'class I, II, and III' used (referring to levels of
Body Mass Index (BMI), described later).
Terminology preferences for how to describe 'having obesity' or 'being obese' and the
level of obesity are on an individual basis; however, there appear to be some commonalities. A
survey of language preferences amongst those seeking bariatric surgery found that 'person with
elevated BMI' and 'person with obesity' were preferable options when addressing a person with
obesity (Pearl et al., 2018). When describing someone with high levels of obesity it was more
preferential to be described as having 'class III obesity' as in comparison to (in order of
decreasing preference) having- a severe BMI, an extreme BMI, severe obesity, extreme obesity,
or the least preferred 'morbid obesity.' Likewise, an online survey focused on weight loss
motivation and language used in a healthcare setting demonstrated that 'weight' and 'unhealthy
weight' were the preferred terms by both those with and without obesity to describe excess
weight with 'morbidly obese,' 'fat,' and 'obese' as least desirable (Puhl et al., 2013). However,
Meadows and Daníelsdóttir (2016) criticize the reliance upon preference surveys for language
usage as they are often based upon prompts that identify weight as a problem a priori, and
participants are found within treatment-seeking settings. In contrast, those outside a weight-loss
setting would have a different conceptualization of their weight. Furthermore, contrary to these
studies, which show 'fat' as the least preferred term (Pearl et al., 2018; Puhl et al., 2013),

12
Meadows and Daníelsdóttir (2016) claimed that the term 'fat' is the preferred term within the fat
acceptance movement. Emphasizing the appropriate use of language when working with persons
with obesity is rooted in the effort to reduce and combat weight biases in research and care
settings (Puhl & Heuer, 2009). This thesis utilizes first person language (i.e., 'person with
obesity') to recognize and acknowledge the stigma associated with having obesity; the intention
of using the term obese and obesity is to ensure that the LTC sector can better attend to the needs
of those with heavier body types.
Body Mass Index
Obesity is generally diagnosed when the accumulated weight in relation to height,
referred to as Body Mass Index (BMI), is over 30 kg/m2. BMI intends to convey possible
increased health risks associated with weighing too much or too little (World Health
Organization, 1995). The standardization and relatively cheap and straightforward measurements
of BMI make it a helpful tool for tracking and comparing population trends for health research
and policy development (Barba et al., 2004).
In 1995, to encourage global reporting and research consistency, the World Health
Organization (WHO) established four uniform BMI categories based upon an aggregation of
adult population health data reflective of weight-dependent health risks observed with various
levels of BMI(kg/m2): underweight (BMI 15-19.9); normal-weight (BMI 20-24.9); overweight
(BMI 25-29.9); and obese (BMI 30 or greater) with each category above and below normalweight, reflecting increased risk to health (World Health Organization, 1995). When analyzed at
a population level, obesity levels suggest a population's increased risk of developing weightdependent health issues such as cardiovascular risk factors, cancers, diabetes, and all-cause
mortality (Guh et al., 2009).

13
Responding to increasing global obesity rates and levels of obesity in 1997 the original
class of obese was expanded into three classes: class I (BMI 30-34.9), class II (BMI 35-39.9),
and class III (BMI ≥ 40) emphasizing the health risks associated with increasing obesity (Nuttall,
2015). The 2020 Canadian Adult Obesity Clinical Practices Guidelines (the Canadian
Guidelines) consider a BMI ≥ 30 as obese and further differentiates the obese category into five
sub-classes, reflecting the increasing number of individuals with higher weights (Rueda-Clausen
et al., 2020). These highest BMI categories immerged largely from bariatric medicine and
surgery research and have been termed severe obesity (class III, BMI≥40), morbid obesity (class
IV, BMI≥50), and super obesity (class V, BMI ≥ 60); with another classification emerging
recently of super-super obesity (BMI ≥70) (Sturm & Hattori, 2013; Wilkinson et al., 2019).
The term 'bariatric' is often used for persons with BMI over 40 kg/m2. As a branch of
medicine, 'bariatric' is defined in Taber's Cyclopedic Medical Dictionary as "the branch of
medicine that deals with prevention, control, and treatment of obesity" (Venes, 2017, p. 244).
This language does not refer to treating a person with obesity but instead is the treatment of
obesity itself. The definition of 'bariatric surgery' provides more details pertaining to the patient:
"[bariatric] surgery is typically used only for those with a body mass index greater than 40 kg/m2
or 35 kg/m2 in the presence of other weight-related health problems, such as hypertension or
diabetes mellitus" (Venes, 2017, pp. 2275–2276). Nursing guide books related to the movement
and transfer of persons of larger size refer to the bariatric patient as those with a BMI over 40 or
who have "large physical dimensions" with "a lack of mobility or other conditions that make
moving and handling difficult" (Thomas et al., 2011, p. 388), and as "those limited in health due
to physical size, health, mobility, and environmental access or those whose weight and/or size

14
interferes with the ability to provide safe and reasonable care" (Bariatric Safe Patient Handling
and Mobility Guidebook Professional Advisory Group, 2015, p. 2).
Body mass index (BMI) serves as a simple to measure and self-reportable value, making
it appealing in its simplicity; however, it is also prone to errors, presents only a static estimation
of excess tissue accumulation, and does not consider tissue type or weight fluctuations. While
relatively simple, height and weight measurements are still vulnerable to differences in
techniques, such as reliance upon an adequately calibrated scale or measuring height standing
versus laying versus sitting (Buys et al., 2014; Yamada et al., 2020). On top of differences in
techniques, BMI information can be collected via self-reporting, which is prone to errors,
including an under-reporting of weight and over-reporting of height, and these errors are
consistent enough that formulas exist to adjust self-reported BMI values (Dutton & McLaren,
2014; O’Neill et al., 2019). Another issue with using BMI is the limited information provided by
the measurement. BMI on its own is a fixed measurement and does not account for a change in
BMI, previous BMI, or time spent with a BMI, which have been suggested as better predictors of
health risks, especially amongst older adults (Baik et al., 2000; Keller & Østbye, 2005; Somes et
al., 2002; Visscher et al., 2001). The inability to account for individual variance in mass
distribution (i.e., location) or type (i.e., muscle versus adipose tissue) is also a drawback of using
BMI (Buys et al., 2014; Nuttall, 2015; Rueda-Clausen et al., 2020; Staiano et al., 2012). On its
own, BMI does not directly identify obesity-related complications, and using a variety of health
metrics when examining an individual's health status is encouraged (Rueda-Clausen et al., 2020;
Wharton et al., 2020).
Other health metrics that supplement BMI include a waist-to-height ratio (WHR), waist
circumference (WC), and more expensive measurements such as body cell mass (BCM), among

15
many others. WHR and WC are also relatively low-cost, simple measurements that, when used
in conjunction with BMI, increase the robustness of health risk assessments, particularly for
older adults when weight becomes redistributed as part of the aging process (Baik et al., 2000;
Corona et al., 2017; Fauziana et al., 2016; Price et al., 2006; Staiano et al., 2012). Unfortunately,
WHR and WC are less routinely obtained than weight and height and are also vulnerable to
issues such as dietary abominable bloating (Rueda-Clausen et al., 2020). Higher technologybased techniques are also available, such as BCM amongst others, which provide a more
accurate and in-depth description of tissue type and location of accumulation; however, it is
expensive to obtain, maintain, and staff such equipment (Alvero-Cruz et al., 2021; Nuttall, 2015;
Volpato et al., 2004). BMI does not provide the most robust information for individual health
and should instead be seen as one of many tools in personal healthcare. However, measurements
of height and weight are simply and cheaply obtained and are used extensively in clinical,
survey, and research settings.
Adjustments of BMI Health Risks
The WHO's BMI health risks are based mainly on Eurocentric population data, yet BMI
health risks are non-homogenous, with different health risks based on ethnicity, age, and gender.
A population's ethnic makeup may require BMI category risk adjustments according to the WHO
and has been explored in obesity-based health research (Barba et al., 2004; S. K. Kumanyika,
2019; Razak et al., 2007)(Barba et al., 2004; S. K. Kumanyika, 2019; Razak et al., 2007). In the
Canadian Guidelines, ethnic populations (non-Eurocentric populations) identified as benefitting
from BMI category risk adjustments are South-, Southeast-, and East Asian ethnicities wherein
higher health risks are placed at lower BMI thresholds, for example, higher risks associated with
having an overweight BMI (Rueda-Clausen et al., 2020). Meanwhile, a need for lower BMI

16
thresholds specific to Aboriginal populations in Canada has been expressed by some studies
(Razak et al., 2007), while others do not find such an adjustment warranted (Lear et al., 2007).
The Canadian Guidelines acknowledge this debate but have kept Aboriginal BMI thresholds in
line with WHO's Eurocentric BMI levels (Rueda-Clausen et al., 2020). In addition to the
considerations of ethnicity, the Canadian Guidelines also highlight the need for caution when
interpreting the health risks of older adults (Rueda-Clausen et al., 2020, p. 3).
Researchers focused on an older adult population have suggested BMI health risks should
be set at higher thresholds for older adults, with overweight and class I obesity treated less
detrimentally (Beck & Damkjaer, 2008; Heiat et al., 2001; Landi et al., 2000; Sánchez-García et
al., 2007; Van Uffelen et al., 2010). There are complex, interactive factors when aging with
obesity, with the literature debating the observed potentially protective role of obesity in older
age against the harmful effects of having obesity (Kiesswetter et al., 2014; Rambod et al., 2020;
Zhang, Field, et al., 2019). The so-called ‘protective factor’ of obesity in older age is primarily
seen as a counter to the associated risk of excess age-related weight loss and malnutrition, and so
a higher BMI appears to provide some protection against the risk of mortality often associated
with older-age frailty (Bosello & Vanzo, 2021; Lindsted & Singh, 1997; Oreopoulos et al., 2009;
Van Uffelen et al., 2010). When reaching older age, there are general changes to the body,
including metabolism, appetite, and physical activity (energy uptake and output) changes termed
the aging process, and it is in the context of the aging process that the role of obesity may play a
protective role. Multiple studies have found that there was a lower risk of mortality in older
adults with obesity in combination with some conditions (e.g., dementia) (Beck & Damkjaer,
2008; Franx et al., 2017; García-Ptacek et al., 2014; Grabowski & Ellis, 2001; Veronese et al.,
2015). However, other studies found the opposite, with higher mortality rates (Heiat et al., 2001;

17
I. Janssen & Mark, 2007; M. Wang et al., 2017) or no significant differences (Baik et al., 2000;
Landi et al., 2000; Price et al., 2006). Likewise, obesity appeared to offer protection against older
age cognitive impairments and developing conditions such as dementia (Rambod et al., 2020;
Zhang, Field, et al., 2019), yet other studies found more pronounced and frequent cognitive
impairments and higher risk of developing dementia (Bowman et al., 2019; Gonçalves
Damascena et al., 2017; Ma et al., 2020). One literature review, in particular, reported that
having obesity earlier in life was associated with a higher risk of developing dementia but having
a higher BMI at an older age conferred a lower risk (Anjum et al., 2018).
The extent of this 'protective factor' is debatable, with some suggesting that the 'survivor
effect' plays a prominent role in the observed phenomenon (Kiesswetter et al., 2014) and, to a
minor extent, age-related height decline. Kiesswetter et al. (2014, p. 1259) describe older adults
with obesity as a "highly selective survivor group relatively resistant towards physical and
cognitive function decline." In other words, older adults with obesity have been subjected to
higher rates of obesity-related-mortality risk throughout their life, so only those with the most
robust genetic, environmental, and socio-economic benefits survived, which results in an overappreciation of the 'protective factors' of having obesity (Kiesswetter et al., 2014). Additionally,
an age-related decrease in height may lead to an overestimation of BMI and its associated health
risks, increasing the appearance of a protective factor (Dey et al., 1999; Sánchez-García et al.,
2007). Finally, obesity is consistently associated with an increased risk for functional and comorbid related disabilities that affect the quality of life (Beck & Damkjaer, 2008; Decaria et al.,
2012; Williamson et al., 2023; Zanandrea et al., 2013; Zhang, Field, et al., 2019). How much of a
protective factor is conferred by having obesity in older age, and how much is a result of
selective survivorship bias, will continue to be an area to be further explored. The importance of

18
understanding whether obesity should be considered less detrimentally in older adults is also
directly related to how obesity in older adults is treated and managed in a healthcare setting.
The treatment of obesity is often weight-loss, with the focus being on losing weight to
lower the risks associated with obesity; however, this weight-loss treatment, especially in older
adults, carries its risks. When reaching older age, there is an associated slowdown of metabolism
and a decrease in energy uptake and output which ultimately results in a redistribution of adipose
tissue and a reduction in lean muscle mass (Dey et al., 1999; Fauziana et al., 2016; Perissinotto et
al., 2002; Shatenstein et al., 2001). The health risks associated with losing weight, or losing too
much weight, therefore, are higher in older adults. When older adults attempt to lose weight, it
can result in unhealthy eating habits that, in conjunction with a decreasing appetite and
metabolism, may lead to malnutrition or under-nutrition, a situation not intuitively associated
with obesity (Bahat et al., 2012; Perissinotto et al., 2002). Since lean muscle mass reduces with
older age, attempting to lose weight without the addition of physical activity to maintain muscle
can amplify the loss of muscle mass with deleterious effects (Allison et al., 1999). There is also
the risk of sarcopenic obesity, a condition defined by relatively low or loss of muscle mass in
combination with obesity, resulting in being "frail-with-obesity" (Bays et al., 2022; Blaum et al.,
2005; Oreopoulos et al., 2009; Wagenaar et al., 2021). The benefits of losing weight seen in the
general population may be less for those with more advanced age (Kopec et al., 2016) and so
rather than focus on weight loss, the strategy proposed for older adults with obesity is geared
towards maintaining body weight while increasing physical fitness and function (Decaria et al.,
2012; Porter Starr et al., 2016). The dangers of losing weight at an older age, in conjunction with
the observed lower risks of mortality and cognition decline (although again, the information is
conflicting on these areas), leads to the argument of having BMI health risk thresholds set higher

19
for older adults. Essentially, at an older age, an overweight and class I obesity BMI should be
regarded less deleteriously with the focus for overall health on maintaining weight alongside
physical activity.
Obesity Prevalence
The number of people with obesity has increased across the globe. Since 1958, adult
obesity has increased three-fold, with greater increases in the highest levels of obesity (Twells et
al., 2020). Between 1981 and 2007, obesity prevalence roughly doubled in each age group
(Public Health Agency of Canada & Canadian Institute for Health Information, 2011). In 2021,
29% of the Canadian population or 8.2 million persons over the age of 12, had obesity, an
increase from 2015 levels, where 26% (i.e., 6.9 million people) had obesity (Statistics Canada,
2022b). One of the more concerning areas is an increase in childhood obesity; in 2016, one in
three adolescents (i.e., those aged six to 17 years) had childhood obesity, an increase from one in
every four in 1985 (Twells et al., 2020). The effect of childhood obesity on subsequent years of
life, including older age, is of concern and not addressed here (Lee et al., 2010). The proportion
of diseases in the Canadian population attributable to obesity rose 138% for men and 60% for
women between 1970 and 2004 (Luo et al., 2007). The rates of obesity continue to increase
amongst older adults (65 years or older), going from 1.3 million older Canadians with obesity
(27%) to 1.8 million (29%) between the years 2015 and 2021(Statistics Canada, 2022b). These
values come from adjusted self-reported BMI levels found in the Canadian Community Health
Survey and do not include institutionalized persons (e.g., persons residing in a LTCF) (Statistics
Canada, 2022b). The rise in obesity is expected to continue; by 2031, over 33% of Canadians are
expected to have obesity (Bancej et al., 2015).

20
Obesity rates are not homogenous across Canada. There are variations between and
within provinces, including amongst urban centers of different sizes and rural areas (I Janssen et
al., 2011; Pouliou et al., 2014; Pouliou & Elliott, 2009; Shields & Tjepkema, 2006; Vanasse et
al., 2006). In 2015, three of the ten provinces had obesity rates of 33% or higher in their older
adult population; by 2021, seven provinces had older-adult obesity rates above 33%; ranging
from the highest level of 39% in New Brunswick to the lowest rate of 25% in British Columbia
(Statistics Canada, 2022b). Obesity rates are generally higher in rural and smaller cities, with the
lowest rates in the largest urban centres (Public Health Agency of Canada, 2020; Shields &
Tjepkema, 2006; Stackhouse, 2019). It is unknown if or how closely these heterogeneous rates
translate into obesity rates in LTCFs across Canada.
Obesity in Long-Term Care (LTC)
An increase in obesity rates in the general population may be expected to translate into an
increase in obesity rates in LTCFs, reflecting patterns across geographic areas (e.g., provincial,
rural, urban, and smaller centers). The rates of obesity in Canadian LTCFs are largely unknown.
Only two studies reported obesity rates in some Canadian LTCFs; the first was a 1997/98 metaanalysis looking at BMI and mortality rates and reported an average obesity prevalence of 16%
in 14 Toronto LTCFs (Veronese et al., 2015). More recently, Shieu et al. (2022) reported an
obesity rate of 17% in Western Canadian LTCFs (BC, Alberta, and Manitoba) in 2016/17. As a
major source of Canadian LTC data, the Canadian Institute for Health Information (CIHI)
collects weight and height measurements; however, it does not report or consider the impact of
obesity or BMIs in their public reports on LTC, in-hospital, or in-community populations
(Canadian Institute for Health Information, 2017c, 2022b, 2023). The only report regarding
obesity found was in reference to bariatric surgeries. (Canadian Institute for Health Information,

21
2014). Research in other countries, especially America, has examined obesity rates in LTCFs.
Drawing inferences from American LTCFs for a Canadian context is difficult as the general
population's obesity prevalence varies between the two nations, with lower overall obesity rates
in Canada (Siddiqi et al., 2015). However, both countries have seen an increase in obesity rates
over the decades, so general changes in American LTCFs may provide insight into how
Canadian LTCFs may be similarly affected.
LTCFs in other countries have seen a non-homogenous increase in obesity rates (Cai et
al., 2013; Felix et al., 2015; Harris et al., 2020; Lapane & Resnik, 2005; MacDonell et al., 2015;
Zhang et al., 2013; Zhang, Field, et al., 2019). A 2015 literature review looking at obesity
prevalence in American LTCFs found an increase from an average of 1% in 1992 to 25% in
2002 (Marihart et al., 2015). Likewise, Zhang, Field, et al. (2019) found that, between 2005 and
2015, the average obesity prevalence in American LTCFs increased from 22% to 28%. Rates of
obesity varied widely both within and between States, but were consistently higher in rural
LTCFs (Harris et al., 2020; Zhang et al., 2013). The variations in obesity rates across facilities
are influenced by the geographic distribution of obesity rates in the general population. However,
that would not account for the wide range seen in New York State, highlighting that multiple
factors influence obesity rates. Obesity rates were also influenced by barriers formed by
differences in facility characteristics (Zhang et al., 2013). While obesity acts as a barrier in
accessing LTC it also serves as a risk factor for needing LTC.
Obesity has been linked to an increased risk of admission to LTC (Felix et al., 2015;
MacDonell et al., 2015; Nizalova et al., 2020; Zizza et al., 2002). Older adults with obesity were
twice as likely to be admitted to American LTCFs than their non-obese counterparts (Marihart et
al., 2015) with obesity at mid-life also found to increase the risk of admission to LTCFs 25 years

22
later (Elkins et al., 2006). Obesity appears to increase the need for LTC mainly due to physical
disabilities, wherein medical advances have extended the number of years of life for those with
obesity, yet those years may be rife with disabilities that require a level of care found in LTCFs
(Decaria et al., 2012; Marihart et al., 2015; Williamson et al., 2023; Zanandrea et al., 2013).
Having obesity also meant needing LTC at an earlier age, with individuals with obesity entering
at younger ages (Ankuda et al., 2017; Cai et al., 2013; Lapane & Resnik, 2005; Shieu et al.,
2022; Temkin-Greener et al., 2020; Williamson et al., 2023; Zhang, Field, et al., 2019). This
increased risk of admission, however, is met with increased obesity barriers, especially when
with higher levels of obesity.
While obesity is seen as a cause for admission to LTCFs, it also simultaneously serves as
a barrier to obtaining that admittance into care (Bradway et al., 2017; Hahler, 2002; Welch,
2016; Zanandrea et al., 2013). For those with the highest obesity, the care required may be so
unlike standard practice that it is suggested that those in the super-super obese group (BMI > 60
kg/m2) should not be placed in Canadian LTCFs at all as their unique needs are beyond the scope
of what is safely available (Welch, 2016). The organizational structure, facility size, and
financial resources appeared to play a role in creating or addressing barriers for those with
obesity. Facilities that can access resources through higher resident numbers featured a higher
prevalence of obesity; such attributes of the facility included higher occupancy rates, higher bed
capacity, multi-facility affiliation, more financial and staffing resources, and a higher resident
mix (Harris et al., 2020; Zhang et al., 2013). Additionally, short-term stays were more likely for
those with obesity, perhaps because facilities are more attracted to persons with obesity planning
for short-term stays due to profit margins that are lost with higher costs and lower
reimbursements for extended stays (Harris et al., 2020; Zhang, Lu, et al., 2019). Negative facility

23
characteristics associated with higher obesity rates included lower quality of care, and lower
efficiency, with persons residing in a LTCF with obesity more likely to be admitted to LTCFs of
poorer quality (Zhang et al., 2013, 2016). Facilities require the capacity and capital to be able to
adequately provide more expensive bariatric equipment (e.g., hospital beds, mobility aids, blood
pressure cuffs, catheters), retrofit older infrastructure (e.g., room and hallway size, reinforced
lifts), and provide higher staffing ratios and specific training (Beitz, 2014; Cai et al., 2013; Felix
et al., 2011; Harris et al., 2018; Rotkoff, 1999). Therefore, facilities with more resources were
able to accept a higher rate of persons with obesity as their case mix, and higher numbers
compensated the higher costs persons with obesity have when in LTCFs. Nevertheless, because
obesity creates barriers and limits the available pool of LTCFs, persons with obesity were also
more likely to enter poorer-quality LTCFs (Zhang et al., 2013).
Bariatric equipment is generally larger, bulkier, more expensive, and is less readily
available in healthcare settings as it is more challenging to acquire, utilize, and store and is only
used by a minority of the population (Boamah et al., 2021; Dockrell & Hurley, 2021; C. Hales et
al., 2020; D. Jones et al., 2020; MacDonell et al., 2015; Welch, 2016; Zhang et al., 2013). While
equipment requirements vary, generally, once a resident reaches a weight of 115 kg (~250 lbs)
larger, reinforced bariatric equipment is utilized to accommodate the girth, weight, and overall
size of persons residing in a LTCF while also assisting in the movement and the mobility of
resident whose bulk may create dangerous situations to patients and staff otherwise (Canadian
Agency for Drugs and Technologies in Health, 2012; Muir & Archer-Heese, 2009). The
coverage of the cost of bariatric equipment varies and may be classified as an additional cost
separate from the norm; for example, in British Columbia, basic wheelchairs are provided for
personal use in LTCFs, yet bariatric wheelchairs are excluded from the definition of a basic

24
wheelchair, as they are considered specialty equipment (British Columbia Ministry of Health,
n.d.). The lack of availability of bariatric equipment and the lack of capacity to safely
accommodate said equipment, in any healthcare setting, including in LTCFs, are significant
barriers for those seeking safe care (Bradway et al., 2017; Caz Hales et al., 2019; Sardani, 2014).
More financially well-off facilities would therefore be more likely to have the capital to obtain,
maintain and retrofit for such equipment.
The purchasing of adequate equipment and the retrofitting of older facilities are
expensive capital undertakings, and many American facilities still struggle to make this
transition (Zhang et al., 2013). Often LTCFs are older buildings, which would require expensive
retrofitting to be able to house the equipment needed to care for persons with obesity, such as
doorway, room, and hallway sizes, ceiling capacities for lifts, and larger bathrooms, amongst
other considerations, such as storing the equipment, emergency preparedness, or elevator
capacities (Bradway et al., 2017; Hahler, 2002; C. Hales et al., 2020; Harris et al., 2018; Lapane
& Resnik, 2005, 2006; Ramme et al., 2015). Such undertakings are both cost-effective and
beneficial for the care staff and the persons residing in a LTCF (Collins et al., 2004), yet not all
facilities are capable of handling an increase in obesity prevalence, let alone meet current
demands (Harris et al., 2018; Marihart et al., 2015; Roblin et al., 2022). Canadian facilities also
vary in their ability to be able to handle bariatric equipment, with some facilities not able to take
bariatric patients at all; however, it is unknown how many facilities have the capacity, how many
require retrofitting, or even if the number of facilities is already adequate for the demand in the
population. The Canadian Standards Association (CSA), a voluntary association engaged in
standards development for healthcare facilities, states that the dimensions and clearance of
rooms, including inpatient rooms, examination rooms, washrooms, and accessible space require

25
planning and retrofitting with the explicit intent of accommodating the equipment and space
required for those weighing 225-453lbs (Canadian Standards Association, 2018; Welch, 2016).
To what extent LTCFs in Canada face the complications of maintaining a separate set of
equipment for bariatric persons residing in a LTCF, including in smaller and rural centers, and
how that impacts individuals attempting to enter LTCFs and those already in LTCFs is unknown,
and is an area for future researchers to explore.
The barriers of obesity when trying to access LTC have been associated with increased
length of hospital stays, which contributes to their deterioration and may even result in becoming
'stranded in hospital' (Bradway et al., 2017; Felix et al., 2016; Miles et al., 2012). Becoming
'stranded in hospital' while waiting for home care or LTC is a phenomenon seen in Canada and
further strains the Canadian healthcare system (Bender & Holyoke, 2018; Costa et al., 2012;
Kuluski et al., 2022). In 2018, Canadian hospitals had 55,000 patients with extended hospital
stays waiting for a bed in a Canadian LTCF, plus half as many waiting for home care services
(Canadian Institute for Health Information, 2019a). This pressure on the healthcare system has
led some provinces to force patients out of hospitals and into LTC up to 150 km away (DeClerq,
2022).Furthermore, refusal to enter into a LTCF when in-hospital also has negative
repercussions, with instances of being discharged from the hospital into a shelter or threatened
with hefty hospital bills, a situation made more common because of the COVID-19 pandemic
(DeClerq, 2022; Mcquillan, 2022). When waiting in Canadian hospitals for LTC admissions
higher levels of obesity were associated with longer lengths of stay (Costa et al., 2012). Persons
with obesity have fewer LTCFs to choose from, as facilities may be unable to accept bariatric
patients or may have the capability but not the availability. The limited stock of adequate
facilities available to persons with obesity, may therefore increase the risk of accepting a spot in

26
a non-preferred LTCF or being forced to enter a LTCF further away from their home (Miles et
al., 2012). Current policies in BC have the option of placing a resident into any LTCF, which
includes outside of their community, with the option of remaining on waitlists for their preferred
LTCF (British Columbia Ministry of Health, n.d.). More research is needed to better understand
how obesity impacts the number of days spent waiting for Canadian LTC while in-community,
in-hospital, or while in a non-preferred LTCF and the distance a Canadian resident must go from
home to find a facility with the capacity and availability for their care needs.
When administrators and staff do accept persons with obesity into a LTCF, they may do
so while holding reservations or weight biases that create a negative or under-prepared
environment (Felix et al., 2011; Caz Hales et al., 2019; Puhl & Heuer, 2009). Persons with
obesity and increasing obesity have a higher risk of needing two+ person assistance when
completing daily living tasks (Felix et al., 2011; Harris et al., 2018; D. Jones et al., 2020;
Rotkoff, 1999) and higher healthcare costs while in LTCFs (Cai et al., 2013; Williamson et al.,
2023; Yang & Zhang, 2014; Zhang et al., 2013). When staffing levels and hours are already
stretched thin, as has been reported in many Canadian LTCFs (MacCourt et al., 2020; Ontario
Ministry of Long-Term Care, 2020), the more extensive assistance required by patients with
obesity is a barrier to acceptance into LTC (Bradway et al., 2017; Felix et al., 2016). Moreover,
the lack of equipment availability or accessibility could mean adapting to available resources by
using more people to assist adding to concerns for the safety of staff and persons residing in a
LTCF as inadequate staff levels and equipment increases the risks of injuries for both staff and
persons residing in a LTCF (Felix et al., 2016; Hahler, 2002; Harris & Castle, 2019; D. Jones et
al., 2020). Staffing hours are generally based per resident; however, regulations are not
consistent across Canada or necessarily based on provincial legislation. For example, BC has no

27
legislation governing LTC staffing hours or type of staff providing care, utilizing instead
provincial guidelines. These guidelines ascribe that each resident receives 3.36 hours of direct
care per day, yet this goal is not always reached, and it also appears to put persons residing in a
LTCF at risk, with 4.1 hours being identified as a minimum for safe care (MacCourt et al., 2020).
Additionally, the inability of funding and staffing algorithms to adjust to two+ person assistance
and higher costs of care consequently results in lower reimbursement for services, directly
impacting facilities' willingness to take in individuals with obesity (Miles et al., 2012).
Addressing these capital and human resources-based barriers is difficult and interweaves
multiple areas of a system already straining to adapt and provide care to a growing population
(Estabrooks et al., 2020; MacCourt et al., 2020).
Age, Obesity and LTC
Older persons residing in a LTCF with obesity are a small minority of their age group.
Research in other countries has also found that persons residing in a LTCF with obesity were
more likely to be younger (Cai et al., 2013; Grabowski et al., 2005; Kuchibhatla et al., 2013;
Temkin-Greener et al., 2020). Shieu et al. (2022) reported higher rates of obesity in younger age
groups (in this case, 51-80 years) residing in Western Canadian LTCFs, which is supported in
other countries LTCFs as well. The sub-population of younger persons residing in LTCFs has
unique care requirements. Hay and Chaudhury (2015) explored the quality of life for younger
persons aged 70 years or below living in LTCFs in British Columbia, finding that younger
persons residing in a LTCF had distinctive needs that required more social, emotional, and
psychological care, that were often not taken into consideration, as care services and activity
programs were geared to an older population. Since LTC is generally tailored toward older
individuals, staff may not have the experience or knowledge to care for younger persons residing

28
in a LTCF, especially those with disabilities and developmental challenges (MacCourt et al.,
2020). Specific to care and management of obesity in LTCFs, younger-older adults in LTCFs
would not benefit from the potential obesity 'protective factors’ associated specifically with the
aging processes previously described in older adults (Bosello & Vanzo, 2021; Lindsted & Singh,
1997; Oreopoulos et al., 2009; Van Uffelen et al., 2010), and would not need adjustments to risk
thresholds at lower obesity levels. The risk of obesity in adults, in general, is well established in
the literature, with a greater risk of mortality, co-morbidities, and disability (Anis et al., 2010;
Guh et al., 2009; Landi et al., 2000; Luo et al., 2007; Rao et al., 2018; C. Wang et al., 2016;
Wilkinson et al., 2019). The management of obesity in LTCFs for this younger-older adult
population would therefore look different from the management of care for older persons
residing in a LTCF with obesity, as it may be more appropriate to emphasize weight loss rather
than weight management.
Health Conditions, Obesity and LTC
There are many conditions in LTCFs; however, dementia and diabetes are two of the
more prominent ones. The prevalence and incidence of dementia increases after the seventh
decade of life, with 12% of Canadians aged 80-85 diagnosed with dementia and twice that for
individuals over 85 (Public Health Agency of Canada, 2017). Dementia continues to be the most
significant contributing factor for needing LTC (Halonen et al., 2019), with 22% of 'stranded in
hospital' Ontarians waiting for LTC or home services while with dementia (Canadian Institute
for Health Information, 2019a). Older persons with obesity have lower rates of having and lower
risks of developing dementia or general cognitive decline (Ankuda et al., 2017; Aslan et al.,
2015; Cai et al., 2013; Dahl et al., 2008), yet other studies point to obesity earlier in life and
higher rates of developing cognitive issues including dementia (Anjum et al., 2018; Ma et al.,

29
2020; C. Wang et al., 2016). Both dementia itself and the treatment for dementia are associated
with weight loss (Bowman et al., 2019; Franx et al., 2017). Persons with an overweight BMI or
obesity may have a partial ‘protective factor’ for starting with higher weight alongside dementia
to allow for some weight loss (de Souto Barreto et al., 2017; García-Ptacek et al., 2014). The
literature has found that persons with obesity have lower rates of dementia when in LTCFs even
when age and other demographics are considered (Ankuda et al., 2017; Cai et al., 2013).
Dementia will continue to be a disease of importance for LTC and increasing the understanding
of a minority population (those with obesity and dementia) will be beneficial for health equity in
LTCFs.
Diabetes is present in a quarter of the LTC population (Canadian Institute for Health
Information, 2022b). The management of diabetes in LTCFs is unique due to its setting. One
study that examined diabetes management in LTCFs highlighted the variety of opinions
physicians had on the intensity of monitoring and management, target levels, and use of clinical
practice guidelines, with a disconnect between expected achievements of diabetes management
and actualization of intentions (Osman et al., 2016). Likewise, Lega et al. (2020) found poor selfreported knowledge of diabetes management amongst LTC nurses, registered dieticians, and
personal support workers. A lack of knowledge of diabetes management was also related to the
overtreatment of frail older adults in LTCFs, as older adults with diabetes need distinct diabetes
treatment from diabetes in young persons (Meneilly et al., 2018). Traditional therapeutic diets
treating diabetes or obesity in older adults increase the risk of frailty and malnutrition (Bahat et
al., 2012; Formiga et al., 2013; Perissinotto et al., 2002). Diabetes will continue to be a
prominent condition in LTCFs and understanding the population most at risk (those with obesity)
will be beneficial.

30
Activities of Daily Living, Obesity and LTC
Activities of daily living (ADLs) are tasks performed in a typical day that allow
independent living and are a common way to track the demands of patients within long-term care
facilities (Canadian Institute for Health Information, 2019b; Harris et al., 2018; Jenkins, 2004;
Lapane & Resnik, 2005; Rao et al., 2018; Rotkoff, 1999). Individuals in-community are
continuously assessed on their ADLs with an inability to perform specific or an accumulation of
tasks, often resulting in referral to further care, such as LTCFs (Venes, 2017, p. 39). Assessing,
quantifying, and tracking an individual's ADL abilities through validated assessments allows for
comparing expected performance against similar individuals and monitoring changes in abilities.
The Resident Assessment Instrument (RAI-MDS 2.0) is utilized by LTCFs participating in
CIHI's Community Care Reporting System (CCRS) (Canadian Institute for Health Information,
2019b).
Individuals with obesity have been found to enter LTC with higher independence in
cognitive-based abilities, especially late-loss abilities such as eating, but were more likely to
exhibit a greater need for extensive assistance with physical-based abilities (Harris et al., 2018;
Kosar et al., 2018; Rao et al., 2018; Rotkoff, 1999; C. Wang et al., 2016; Zhang, Field, et al.,
2019). Conversely, other studies have found that after considering cognitive status, there were no
associations between ADL scores and obesity in older adults (Borda et al., 2021; Kiesswetter et
al., 2014). Comparing ADL independence levels of persons newly residing in a LTCFs will
provide information on the utilization of resources (two+ person) and may lend some insight into
the impact of obesity on independence.

31
Equity Considerations
Equity in health is about eliminating unnecessary/avoidable, and unfair/unjust
differences in health among population groups and communities.
-Patychuk and Seskar-Hencic, 2008, p. 2
Approaching healthcare with an equity lens requires 1) the identification of priority
populations and the populations' needs, 2) understanding the unique barriers and burdens faced
in meeting those needs, and subsequently, 3) what policies, interventions, programming, or
changes to social and environmental conditions can be implemented to minimize barriers and
burdens, and meet those needs (Patychuk & Seskar-Hencic, 2008). Before healthcare policies
and interventions can be implemented to their fullest potential and to better capture and
acknowledge barriers and burdens faced, the identification of priority populations requires
activities such as surveillance research that produce a ‘broad picture’ of the population in
question (Patychuk & Seskar-Hencic, 2008).
The health barriers and burdens of persons with obesity are well-studied in the general
population (Ankuda et al., 2017; Phelan et al., 2015; Puhl & Heuer, 2009; Sutin et al., 2015). The
population with obesity may face common deficiencies in health equity when interacting with
the healthcare system, including LTC (Meadows & Daníelsdóttir, 2016). Research surrounding
individuals with obesity in LTCFs in other countries has demonstrated that those with obesity
consistently show poorer health and face more significant barriers in both entering LTC and
obtaining quality care once admitted (Bradway et al., 2008; Caz Hales et al., 2019; Marihart et
al., 2015; Porter Starr et al., 2014; Zanandrea et al., 2013). Such observations suggest that those
with obesity in LTCFs should be considered a potential population of interest when ensuring
equity in health, and this should be extended to Canadian LTC.

32
Weight Bias
The understandings around the causes of obesity in healthcare and literature have evolved
to include not only behaviour and lifestyle factors in the control of individuals but also socioeconomic factors, obesogenic-environments, and genetic determinants that are out of an
individual’s control (O’Neill et al., 2019). These concepts challenge the previously and often still
prevailing conceptualization of obesity as a condition of a character flaw, such as being lazy or
lacking willpower (Pearl & Puhl, 2018; Pila et al., 2016). Negative assumptions and judgments
about an individual’s character, stemming from an individual’s weight, are termed ‘weight bias.’
Weight biasness can be held by any member of society, including internally or by healthcare
providers, and can be built into systems and settings.
Weight bias and weight bias internalization occur in both explicit and implicit scenarios
in healthcare settings through stigmatization and stereotypes that, in turn, then influence the
behaviours of both the healthcare provider and the person with obesity, consequently negatively
impacting the patient’s physical and mental health (Jackson et al., 2014; Pearl & Puhl, 2018;
Phelan et al., 2015; Pila et al., 2016; Sutin et al., 2015). Healthcare providers may exhibit explicit
weight bias, such as negative attitudes, language used or blameworthy causes of obesity, (Hauff
et al., 2020; Oliver et al., 2021; Phelan et al., 2015; Puhl & Heuer, 2009; Zevin et al., 2021).
Healthcare providers may also see obesity as the paramount issue regardless of patients’
concerns or approach obesity management in unhelpful ways, negatively impacting patients’
healthcare experiences (Meadows & Daníelsdóttir, 2016; Puhl & Heuer, 2009).
Meanwhile, implicit bias is manifested in environmental settings that negatively affect
the perceived acceptance of persons with obesity and instead emphasize that they, as a product of
their body type, are not the norm (Phelan et al., 2015). Indirect weight bias occurs in the

33
healthcare setting through deficits in appropriate supplies, equipment, staffing and environmental
structures, creating a setting that negatively affects the feelings of acceptance of persons with
obesity, reducing the quality of care and contributing to the internalization of weight biasness
(Oliver et al., 2021; Pearl & Puhl, 2018; Ramme et al., 2015). Balancing the need to reduce the
harmful psychological and social effects of weight biasness while acknowledging the
physiological risk factors associated with excess weight is essential to obesity management
(Phelan et al., 2015). Nevertheless, healthcare providers may feel unprepared to manage obesity
(Katz et al., 2022; Zevin et al., 2021).
By utilizing appropriate language and acknowledging the differences required in health
settings for persons with obesity entering long-term care, this thesis aims to reduce settingsbased weight bias and discrimination; making it part of the norm to consider differences in BMI
allows for settings to strive for equitable healthcare by outwardly and explicitly acknowledging
differences in care needs. While obesity has been studied in the general Canadian population,
there is scarce information available regarding the prevalence or effects of having obesity in
institutional settings such as Canadian LTCFs. Analyzing demographic and clinical data
collected during initial assessments from hundreds of LTCFs across Canada over the past
decade, this thesis provides the initial 'broad picture' of the population with obesity as they enter
LTC. Understanding the healthcare needs of those with obesity is the first step towards
physically safer, less stigmatized, and more inclusive environments.

34
Chapter Three: Methods
Data Sources
This thesis intends to fill gaps in research surrounding Canadian obesity rates in LTCFs,
with a focus on the population entering LTC. Individuals who enter a LTCF for the first time are
at a major transition point in life. The population transitioning into LTC is not homogenous, and
this thesis will consider variations in demographic characteristics, health conditions, and care
needs.
Most of the data reported in this thesis originates from micro-data contained within the
Continuing Care Reporting System (CCRS), operated by the Canadian Institute for Health
Information (CIHI). Launched in 2003, the CCRS is a data-holding system that collects and
reports information collected through the Resident Assessment Instrument Minimum Data Set
2.0 Canadian Version (RAI-MDS 2.0) (referred to interchangeably as 'the initial assessment')
(InterRAI Corporation & Canadian Institute for Health Information, 2012). Developed by
interRAI, a not-for-profit international research network, and modified by CIHI for Canadian
use, the RAI-MDS 2.0 is a standardized clinical assessment of patients requiring continuing care
(Canadian Institute for Health Information, 2017a). The CCRS data includes Canadian long-term
care facilities (LTCFs) that have 24-hour nursing available with publicly funded/subsidized beds
(Canadian Institute for Health Information, 2019b). The CCRS reported 192,670 persons
residing in LTCFs in the fiscal year 2016-17, which accounted for approximately 75% of all
persons residing in Canadian LTCFs (Canadian Institute for Health Information, 2017c; Statistics
Canada, 2017a). CIHI regularly publishes reports and makes data publicly available regarding
demographics and clinical information of persons residing in LTCFs (Canadian Institute for
Health Information, 2017a, 2017b). The CCRS micro-data is therefore a useful resource that

35
captures demographic and clinical information on a majority of persons residing in a LTCF
through validated assessments.
When entering a participating LTCF initial assessments were required to be completed
within 14 days of admission to a facility (Canadian Institute for Health Information, 2019b). The
data request limited assessments to only the first initial assessment per individual newly admitted
to a LTCF by excluding multiple assessments, assessments completed 30 days or more after
admission date, and any assessment completed for re-entry, discharge, transfer, or any purpose
other than initial entrance (e.g., annual, major changes in ability). Through their internal
processes, CIHI determined the level of de-identification required before the release of the data
set to ensure confidentiality, this included withholding some demographic information (e.g.,
marital status), amalgamating some answers (e.g., education), or providing categorized groups
(e.g., age groups).
The key characteristic in this thesis was BMI, which was calculated and provided by
CIHI categorically. The only facility characteristic obtained was the province or territory of the
facility. The key demographic variables included in this report are weight, age, sex, primary
language, and location of last residence. Clinical information variables comprise presence of
chronic health conditions along with performance and assistance levels of activities of daily
living (ADLs)
This thesis also includes information obtained from previous literature regarding the
obesity rates and rates of health condition dyads found amongst in-community older Canadians.
The obesity rates amongst persons newly residing in a LTCF were compared to the rates of
obesity amongst older adults living in the general population (i.e., not in LTCFs) and these incommunity rates were obtained through the research produced by Lytvyak et al. (2022) that

36
utilized Statistics Canada’s 2005-2018 Canadian Community Health Surveys (CCHS). Likewise,
the rates of health condition dyads in the newly entered LTC population were compared to incommunity rates from Statistics Canada’s 2008 Canadian Survey of Experiences with Primary
Health Care (CSEPHC) as reported by CIHI (Canadian Institute for Health Information, 2011).
Ethics
The Research Ethics Board (REB) of the University of Northern British Columbia
determined this research as not requiring REB approval as the project worked with nonidentifiable data that is solely accessed through CIHI, with no external linkages, of which CIHI’s
system manages the privacy and security.
Research Sample
The population of interest was defined as all those entering a Canadian long-term care
facility (LTCF) for the first time. The reference population was limited to newly entered persons
residing in a CIHI participating LTCF an initial entrance between January 1, 2010, and
December 31, 2020, and not entering from another LTCF.
Research Design
The study utilized retroactively obtained, consecutive cross-sectional data previously
collected during the initial assessment between 2010-2020 inclusive. This study examined the
initial assessment data to create a descriptive account of the newly entered LTC population with
a focus on the differences between the sub-populations defined by their obesity or BMI status.
The annual ‘incidence’ of obesity and BMI statuses among those recently admitted to LTC were
calculated. Provincial and territory obesity rates were also examined as a characteristic of the
facilities. Utilizing the entire populations newly entered between 2010-2020, as defined by their
BMI, a demographic profile and analysis of health and ADL indicators was created. The

37
demographic variables considered were age, sex, primary language spoken, and last location of
residence. These are described in more detail in 3.4.3. Health status was evaluated with
frequencies of chronic conditions, multiple conditions, and most common dyads of conditions.
This is described in more detail in section 3.4.4. Finally, ADLs were summarized as to whether
an individual could or could not perform independently, and whether or not two+-person
assistance was provided. This is described in more detail in section 3.4.5. Combined, these
variables provide a ‘broad picture’ of the population newly entered into participating LTCFs
while highlighting the difference between population with obesity and other BMIs.
Initial Data and Clean-up
The data request to CIHI yielded a total of 448,337 unique initial assessments. In the
initial screening of assessments 4,033 (1%) were removed due to missing weight (2,121) or less
than 10 kg (1,922), secondly, 87,414 cases (20%) had an entry service type listed as residential
care and were removed, and finally 6,542 cases (2%) were removed due to missing BMI records.
After this screening, there were 350,348 assessments utilized for analyses. A further breakdown
of the removal based on entry service type and missing BMI follows.
The service type of the admitting facility was collected with ten options but provided in
four (private home/apt with or without home care, inpatient, residential care, and ambulatory
health services or other services).With a high proportion of the original assessments entering
from residential care (n=87,414), the distribution of BMI categories was explored for these
assessments and found to largely mirror the distribution of the total population (Figure 1). These
assessments were then removed from the population.

38
Figure 1
Distribution of Body Mass Index (BMI) of All Persons Newly Residing in a Long-term Care
Facility (N=356,890) and Persons Newly Residing in a Long-term Care Facility Entering from
Residential Care (n=87,414), 2010-2020
45
Total Population

Propotion of the group (%)

40

Entering From Residential Care

35
30
25
20
15
10
5
0
<18.5

18.5-24.9

25.0-29.9
30.0-34.9
35.0-39.9
Body Mass Index (BMI) Category

40.0+

Assessments with a missing BMI, but with a valid weight, were initially to be included in
the 'weight only' analysis (n= 6,542). However, when exploring the distribution of missing BMI
by weight categories there was a notable issue for the lightest category (<20kg), and the heaviest
category (>120 kg), especially the ≥ 200 kg category (Figure 2). The more extreme weights had
relatively high numbers of missing BMIs compared to the number of individuals within the
category. Of the persons newly residing in a LTCF, 96% (n= 1,126) in the heaviest weight
category (≥ 200 kg) and 50% in the lightest category (<20kg) did not have a valid BMI. The
likelihood of an adult weighing under 20 kg or over 200 kg is low, so the spikes at the more
extreme categories are most likely due to input errors. As such, any results would be greatly
skewed in these relatively small categories. Overall, there were less than 5% of persons newly
residing in a LTCF with a missing BMI, so these assessments were also excluded from the
weight-only analysis.

39

70000

1200

60000

1000

50000

800

40000
600
30000
400

20000

200

10000

200=+

190-199.9

180-189.9

170-179.9

160-169.9

150-159.9

140-149.9

130-139.9

120-129.9

110-119.9

100-109.9

90-99.9

80-89.9

70-79.9

60-69.9

50-59.9

40-49.9

30-39.9

20-29.9

0

10-19.9

0

[Light Bars]
Number of Residents Without BMI

[Dark Bars}
Number of Residents With Valid BMI

Figure 2
Valid and Missing Body Mass Index (BMI) by Weight Category of Persons Newly Residing in a
Long-term Care Facility (N=350,348), 2010-2020

Weight Category (kg)

Facility Characteristics
The expansion and varying provincial commitment levels to the CCRSs over time may
affect longitudinal results, so the interpretation of annual trends occurring between 2010 and
2020 should be done with caution (Canadian Institute for Health Information, 2019b). Provincial
and Territory information for Alberta, British Columbia, and Ontario, were provided
independently, however, largely due to relatively small numbers of participating facilities, the
'Other' group was an amalgamation of Manitoba, Newfoundland and Labrador, Nova Scotia,
Saskatchewan, and the Yukon Territory (Table 1). Most provinces had full commitment to the
CCRS program, however Saskatchewan and Manitoba only had partial commitment (Canadian
Institute for Health Information, 2020c). Of note, Saskatchewan had no participating facilities in

40
FY 20/21 but had +130 facilities submitting the years previous. A separate data request would
have been required to obtain the information on 2010-2015, however, due to time constraints and
previous delays this was not undertaken. Table 1 shows the publicly available data for the
number of participating facilities.
Table 1
Number of Participating Long-Term Care Facilities by Fiscal Year, 2016/17-2020/21
Province
Alberta
BC
Ontario
‘Other’ group
Total

16/17
13 (174)
22 (297)
47 (626)
18 (235)
100 (1332)

Fiscal Year % (n)
17/18
18/19
19/20
13 (174)
13 (177)
14 (180)
22 (298)
22 (297)
23 (299)
47 (626)
47 (626)
47 (623)
18 (233)
17 (219)
16 (216)
100 (1331)
100 (1319)
100 (1318)

20/21
15 (181)
25 (299)
53 (620)
7 (79)
100 (1179)

Fiscal Year % (n)
Province and Territory in
the ‘Other’ group
Manitoba
Newfoundland and Labrador
Nova Scotia
Saskatchewan
The Yukon
Total ‘Other’ group

16/17

17/18

18/19

19/20

20/21

16 (37)
17 (39)
0 (0)
66 (154)
2 (5)
100 (235)

17 (39)
15 (35)
2 (2)
65 (152)
2 (5)
100 (233)

18 (39)
16 (35)
0 (0)
64 (140)
2 (5)
100 (219)

18 (39)
16 (35)
0 (0)
63 (137)
2 (5)
100 (216)

48 (38)
46 (36)
0 (0)
0 (0)
6 (5)
100 (79)

Demographic Variables
The initial assessments provided various variables for analysis. CIHI limited some variable
information due to confidentiality concerns. BMI and weight-only were used for incidence
analyses. CIHI provided BMI using the WHO's six categories. Class III obesity is the highest
category provided, the low number of individuals in and above this category prevented the use of
higher obesity. Weight was provided in kilograms to the first decimal and transformed into
<115k, 115-134.9, 135-154.9, ≥155.

41
Alongside BMI, demographic variables included age, sex, primary language, and location
of last residence. Categories. Age was provided in 5-year categories, with <20 years as the
youngest group, and ≥ 85 years as the oldest, and these were transformed into ten-year age
groups (<50, 50-59, 60-69, 70-79, ≥80). The variable of sex utilized male, female and ‘other’.
Primary language spoken was recorded in the assessment; however, this variable was provided
dichotomously as speaking one of the official languages (English/French) or not doing so.
Finally, the location of last residence was provided as either rural or urban and was based on the
most recent postal code before entering LTC. CIHI defined rural and urban utilizing Statistics
Canada's Statistical Area Classification (SAC) with urban defined as SAC Types 1-3 (census
metropolitan areas (CMAs) and census agglomerations (CAs) and rural defined as SAC Types 48 (areas outside CMAs and CAs) (Canadian Institute for Health Information, 2022a).
Morbidity and Multiple Morbidities
Multiple indexes have been utilized by surveys and research to account for the impact of
accumulation and different combinations of health conditions, with indexes counting from four
to upwards of fifteen conditions. Indexes used in research by Tooth et al. (2008) on multimorbidities and ADLs, and Halonen et al.'s (2019) research on multi-morbidities and LTC
admissions along with indexes used in three Canadian surveys were compared for overlapping
conditions to create an index for this thesis. The three surveys were, starting with most recent,
the Canadian Survey on Access to Health Care and Pharmaceuticals During the Pandemic
(SAHCPDP), Barriers to Care for People with Chronic Health Conditions (BCPCHC) and the
Canadian Survey of Experiences with Primary Health Care (CSE-PHC) (Statistics Canada, 2009,
2012, 2021). Finally, some of the conditions recorded in the CRRS data set from CIHI were
combined to better fit definitions within the developed index (see list below). Based on this index

42
a count of multiple morbidities amongst persons newly residing in a LTCF was developed.The
final list of 14 conditions developed for this multi-morbidity index was:
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Hypertension (high blood pressure),
Dementia/Alzheimer's (combined),
Arthritis,
Diabetes Mellitus,
Osteoporosis,
Depression,
Stroke,
Emphysema/COPD,
Anemia,
Cancer,
Asthma,
Liver Disease,
Hip Fracture,
Heart Disease (a combination of CIHI's RAI-MDS 2.0 congestive heart failure, other
cardiovascular diseases, and arteriosclerotic heart disease (ASHD))
For those conditions that were combined (i.e., Heart Disease is the combination of the

RAI-MDS 2.0’s conditions of congestive heart failure, other cardiovascular diseases, and
arteriosclerotic heart disease (ASHD)), a single variable was created called Heart Disease.
Having one or more of those three listed conditions resulted in a single positive result for the
Heart Disease variable. The same was done for the Dementia/Alzheimer’s variable. This index of
conditions was utilized to provide a count of multi-morbidities seen in the population of persons
newly residing in LTCFs, and to explore if there are differences in the number and rates of multimorbidities by BMI status.
Activities of Daily Living - Independence
For simplicity, the independence levels of persons newly residing in a LTCF were
transformed into dichotomous readings of whether or not an individual performed the activity
independently. Being independent was defined as "No help or oversight or help/oversight
provided only 1 or 2 times during last 7 days"(Canadian Institute for Health Information, 2016).

43
Literature looking at obesity in American LTCFs found an increase in two+ person physical
assistance for those with obesity, namely for activities with a larger physical component (e.g.,
bed mobility) (Harris et al., 2018; Zhang, Field, et al., 2019). Assistance provided for ADLs was
limited to whether or not two+ person assistance was required.
Statistical Tests
Two separate analyses were conducted for each point of interest. The first compared the
proportions of those with obesity (BMI ≥ 30 kg/m2) to those without obesity. The second
analysis used the six WHO BMI categories, with normal BMI situated as the reference group
against each of the other 'non-normal' BMI categories. Statistical analysis was performed using
SPSS version 28 (IBM Corp., 2021). The data was populated into Cross-Tabulation tables and
Chi-squared tests, with significance levels of p ≤ 0.001, were utilized for these assessments (Polit
& Beck, 2017, p. 392).
Proportional ratios (PRs) on the line graphs were utilized to visually represent the
differences of independence for multiple ADLs between those with and without obesity, while
also taking dementia into account. The PRs also allowed for the comparison across multiple
BMIs, with and without dementia. Obesity PRs were first calculated by dividing the proportion
of persons newly residing in a LTCF with obesity operating at an independent level by the
proportion of persons newly residing in a LTCF without obesity operating at an independent
level. Secondly, when using the six BMI categories, persons newly residing in a LTCF with a
normal BMI were set as the reference population, and the BMI PRs were calculated for each
"non-normal" BMI category by dividing the proportion of independence of the BMI category
over the reference categories' independence proportion. Each calculation had two PRs created for
each of their ADLs: one PR for those with dementia (x) and one PR for those without dementia

44
(o). A PR significantly greater than 1.0 indicates a higher proportion of independence amongst
those with obesity, a PR significantly less than 1.0 indicates lower independence, and a PR of 1.0
indicates no difference. In the case of the six BMI categories, the PR values refer to the
performance level of the 'non-normal' BMI in relation to the reference group. Secondly, the
length between the x and o visually showcases the relative differences seen between the
populations with and without dementia. Finally, these lengths and PR positions can be compared
between the BMI categories.

45
Chapter Four: Results
Obesity rates in the Canadian general population have been increasing over the past
century. As the population ages, little is known about how the rising number of obese older
adults will affect the long-term care (LTC) population. Since research into obesity in Canadian
LTC is sparse, the focus here is to produce information that may be used to inform future
research and policy about LTC capacity and resources. This will be achieved through an
exploration of rates of obesity recorded in initial assessments of persons newly residing in a
long-term care facility (LTCF) (N=340,348) over a 10-year period (2010-2020), and the
development of a profile that examines the demographic characteristics, health conditions, and
levels of independence relative to their Body Mass Index (BMI) upon entry to a LTCF. The
prevalence of obesity in LTCFs will be influenced by the influx of new individuals into LTCFs,
so it is worthwhile to provide an estimate of this influence and how it changes over time.
Individuals transitioning into the LTC population have been under different social and
environmental influences as compared to those living in LTCFs and represent a population that
could be a target for policies and programs that delay or prevent LTC admission. Examining
persons newly residing in a LTCF over time offers an opportunity to identify broader societal
changes (e.g., rising rates of obesity) and the implications these may have for LTC now and in
the future.
Assessment Frequencies
The number of first initial assessments remained relatively constant, with a slight
increase in numbers between 2010 and 2019 (Figure 3). There is a notable drop in the number of
assessments between 2019 to 2020, where the number of assessments decreases by 9,646 or by
30% of the total first initial assessments in 2019. This is most likely due to a combination of the

46
COVID-19 pandemic and the withdrawal of Saskatchewan from the program in 2020. This
pattern was also seen at the provincial/territorial level, with relative stability over the 9-year
period and a formidable drop in numbers for each group (Figure 4). Most notably in 2020 there
was a 41% drop in first initial assessments in Ontario and 36% in the ‘Other’ group.
Figure 3
Annual Frequency of First Initial Assessment of Persons Newly Residing in a Long-term Care
Facility (N=350,348), 2010-2020

Number of First Initial
Assessments

40000
35000

31577

31482

29581

30358

32527

34958

33630

34096

34743

33521

30000
25000

23875

20000
15000
10000
5000
0
2010

2011

2012

2013

2014

2015

Year

2016

2017

2018

2019

2020

Number of First Initial Assessments

Figure 4
Annual Provincial/ Territorial Frequencies of First Initial Assessment of Persons Newly
Residing in a Long-term Care Facility (N=350,348), 2010-2020
Alberta

25000

BC

Ontario

Other

20000
15000
10000
5000
0
2010

2011

2012

2013

2014

2015

Year

2016

2017

2018

2019

Note. Other = Manitoba, Newfoundland and Labrador, Nova Scotia, Saskatchewan, and the Yukon.

2020

47
Profile of Persons Newly Residing in a LTCF (2010-2020)
Between 2010 and 2020, inclusive, there were 350,348 unique initial assessments
submitted from LTCFs that participated in the Continue Care Reporting System (CCRS). The
profile developed of those newly residing in a LTCF showed an older-adult population, with
68% entering at the age of 80 or older, and a further 20% entering between the ages of 70 and 79.
The population was predominantly female (61%, n=214,497), had a primary language of either
English or French (86%, n=302,212), and had a previous primary residence in an urban area
(84%, n=271,427). Obesity was present in 19% of the population, with 12% having class I, 4%
having class II and 3% having class IIII obesity. Much of the population had hypertension (i.e.,
high blood pressure) (61%, n=212,511), or dementia/Alzheimer’s (54%, n=190,415). With
arthritis (35%, n=123,708), diabetes (26%, n=91,809), osteoporosis (22%, n=76,020) and
depression (22%, n=75,829) the next most common conditions. A full list of the rates of chronic
conditions can be found in Appendices 1-2. Most (n=301,314), or 86%, of the persons newly
residing in a LTCFs also entered with multi-morbidities (two+ conditions). Finally, nearly onethird of the sample population required two or more people to assist in performing the ADLs of
transfer (33%, n=116,654), toileting (33%, n=114,877), or bathing (30%, 105,858). Meanwhile,
one-third of the population were noted to perform at an independent level when undertaking the
activities of eating (34%, n=120,365) and bed mobility (32%, n=110,464). A full list of the
assistance provided, and self-performance levels of all ADLs, are provided in Appendices 3-6.
Incidence
This section provides incidence rates of persons newly residing in a LTCF with obesity
(i.e., BMI ≥ 30 kg/m2) to those entering LTCFs without obesity (i.e., BMI <30 kg/m2), as well as
the rates across the World Health Organization's (WHO) BMI categories, including the three

48
classes of obese BMIs. For additional comparison, the prevalence of obesity rates for older adults
residing in community settings are also included. Additionally, obesity rates amongst the newly
entered LTC population are examined across available information for provincial and territorial
location. Finally, an analysis of the incidence of persons newly residing in a LTCF at risk of
requiring specialized bariatric equipment is provided.
Frequency of Obesity
Obesity was present in 19% (n=66,508) of the 350,358 individuals entering LTC between
2010-2020 (Figure 5). The majority of individuals entering LTCFs with obesity were in the class
I category (n=41,279, or 63% of those with obesity), while those with more extreme obesity
levels (classes II and III) accounted for 7% (n=25,229) of persons newly residing in a LTCF over
this time period.
Figure 5
Persons Newly Residing in a Long-term Care Facility by Body Mass Index (BMI) Category
(N=350,348), 2010-2020
Normal
42%

Underweight
11%

Class III
3%
Class II
4%
Class I
12%

Total (N) = 350,348

Overweight
28%

49
Incidence of Obesity
The incidence of obesity (per 10,000) generally increased over the 10-year period, with
the incidence in 2019 being 13% higher than 2010 levels. The only decrease occurred in 2020,
where the incidence dropped by 9% from the previous year (Figure 6). The COVID-19 pandemic
had a profound impact on persons living in LTCFs and facilities in 2020. As such, the figures for
2020 may be regarded as an anomaly. Overall, there was a direct relationship between higher
BMI categories and greater increases in incidence levels (Figure 6). The share of newly entered
individuals categorized with obesity classes I, II and III increased 9%, 15% and 22% respectively
between 2010 and 2019. Again, the intake in 2020 was an exception, where there was a decrease
in the share of persons newly residing in a LTCF categorized as obese.
Figure 6
Annual Rates of Body Mass Index (BMI) Amongst Persons Newly Residing in a Long-term Care
Facility (N=350,348), 2010-2020
Obese
Underweight
Class I

Incidence of Residents Who Newly Entered a Long-Term
Care Facilitiy (per 10,000)

5000
4500

Blank 1
Normal
Class II

Blank 2
Overweight
Class III

4000
3500
3000
2500
2000
1500
1000
500
0
2010

2011

2012

2013

2014

2015
Year

2016

2017

2018

2019

2020

50
Provincial Incidence of Obesity
As discussed in the methods chapter, the CCRS dataset from CIHI only allow for certain
provincial and territorial comparisons. The category ‘Other’ refers to the four provinces and one
territory that are included in the CCRS dataset from CIHI but had too few facilities to allow for
the release of provincial or territorial identifiers. This 'Other' group includes the Yukon territory,
and the provinces of Manitoba, Newfoundland and Labrador, Nova Scotia, and Saskatchewan.
The majority of the newly entered population was based in Ontario (n=215,026 or 63% of newly
entered individuals). The proportion of the newly entered population with obesity and the
distribution of BMI categories were generally similar between provinces (Table 2). The
exception was BC, which had a slightly lower rate of obesity overall and in each class of obesity.
Table 2
Frequencies of Body Mass Index (BMI) Categories of Persons Newly Residing in a Long-term
Care Facility by Geographical Group (N=350,348), 2010-2020
BMI Category

Province/Territory %(n)
Alberta
BC
(15%, n=50,750) (15%, n=51,412)
% (n)
% (n)

Obesity
Non-Obese
Obese
BMI
Underweight
Normal
Overweight
Class I
Class II
Class III
Total

Ontario
(61% n=215,026)
% (n)

‘Other’
(10%, n=33,735)
% (n)

82 (41,034)
18 (9,041)

86 (44,438)
14 (7,074)

80 (171,468)
20 (43,558)

80 (26,900)
20 (6,835)

12 (6,111)
43 (21,413)
27 (13,510)
11 (5,547)
4 (2,019)
3 (1,475)
100 (50,750)

13 (6,906)
46 (23,846)
27 (13,686)
9 (4,614)
3 (1,431)
2 (1,029)
100 (51,412)

10 (22,130)
41 (87,366)
29 (61,972)
12 (26,876)
5 (9,858)
3 (6,824)
100 (215,026)

10 (3,524)
40 (13,599)
29 (9,777)
13 (4,242)
4 (1,481)
3 (1,112)
100 (33,735)

Note. a) ‘Other’= Manitoba, Newfoundland and Labrador, Nova Scotia, Saskatchewan, and the Yukon.

51
Over the ten-year period (2010-2020), obesity (BMI ≥ 30) incidence rates showed a
general increase in each geographical category, with notable decreases in 2020 observed in all
regions represented (Figure 7). British Columbia (BC) had the lowest incidence of obesity each
year while Ontario and the ‘Other’ group category tended to record the highest incidences of
obesity over the ten-year period.
Figure 7
Annual Rates of Obesity Amongst Persons Newly Residing in a Long-term Care Facility by
Geographical Group (N=350,348), 2010-2020

Incidence of Residents Entering Long-Term Care Facilities with
Obesity (per 10,000)

Total Incoming Population

Alberta

British Columbia

Other

Ontario

2510

2010

1510

1010

510

10
2010

2011

2012

2013

2014

2015
Year

2016

2017

2018

2019

2020

Note. a) 'Other' group = Manitoba, Newfoundland and Labrador, Nova Scotia, Saskatchewan, and the Yukon.

A further examination of the changes in incidences for the three classes of obesity are
presented as trend lines in Figure 8. The trend lines indicate that the 'Other' group geographical
category observed the greatest increases in each of the classes of obesity, with class III

52
increasing by 55%. BC saw the lowest growth in each of the classes of obesity, where those with
class I obesity only increased by 12%, while the shares of those with class II and III obesity
remained stable. In Alberta, BC, and Ontario, the highest rates of growth were amongst newly
entered individuals with class I obesity, while the highest rates of growth in the 'Other' category
was persons newly residing in a LTCF with class III obesity.
Figure 8
Trend Lines of Obese Classes Amongst Persons Newly Residing in a Long-term Care Facility by
Geographical Group (N=350,348), 2010-2020
Alberta
Class I

Incidence of Residents Entering Long-term Care
Facilities with obesity (per 10,000)

1400

British Columbia
CLASS II

Other
CLASS II

Ontario

1300
1200
1100
1000
900
800
700
600
500
400
300
200
100
2010

2011

2012

2013

2014

2015

Year

2016

2017

2018

2019

2020

Note. Other = Manitoba, Newfoundland and Labrador, Nova Scotia, Saskatchewan, and the Yukon.

Incidence of Persons Newly Residing in a Long-term Care Facility Weighing 115 Kg or More
The Body Mass Index (BMI), and its categories of obesity, does not give a full account of
the presence of heavier persons newly residing in a LTCF. Regardless of BMI, heavier
individuals are at greater risk of requiring costly bariatric equipment and facility

53
accommodations. Bariatric equipment is generally recommended for those that have a weight at
or above 115 kg (approx. 250 lbs). Those weighing 115 kg or more accounted for a very small
proportion of the newly entered LTC population (1.7% of those entering between 2010-2020,
(n=5,930)). The incidence of persons newly residing in a LTCF in this weight category however
increased by 47% over the 10-year period (Figure 9). Amongst those entering with a weight ≥
115 kg, over two thirds were in the 115-134.9 kg group (n=3,896), and about 20% weighed
between 135 and 154.9 kg (n=1,279). The incidence of those weighing between 115-134.9 kg
increased the most (56%), followed by those weighing between 135-154.9 kg (49%).

Incidence of Weight Category per 10,000

Figure 9
Annual Rates of Individuals at Risk of Needing Bariatric Equipment Amongst Persons Newly
Residing in a Long-term Care Facility (N=350,348), 2010-2020
≥ 115
115-134.9
135-154.9
≥ 155

200

150

140

144

139

205
183
162

100

50

0

91

93

29

28

32

35

22

24

14

18

2010

2011

2012

2013

89

191
179

168

141
107

206

112

121

135

139

131

115

88

28
27
2014

37

42

41

45

42

40

18

20

23

25

24

20

2015
Year

2016

2017

2018

2019

2020

Summary of Incidence of Obesity
Incidence of obesity remained relatively constant over the 10-year period (2010-2020),
although rates of growth (while modest) were highest in those with class II and III obesity. The

54
year 2020 stood out as unique as it was the only year-on-year where a decrease in obesity
incidence was observed. This is most likely related to the onset of the COVID-19 pandemic
within Canada. The moderate increase of obesity, and higher rates in class II and class III, was
generally reflected in provincial and territorial rates. While Ontario had the highest levels of
incidence and BC the lowest, rates of growth remained comparable with Alberta. The 'Other'
category did exhibit higher rates of growth in class I and class III obesity. When considering
only weight as a characteristic of persons newly residing in a LTCF, there was notable increase
in incidence, with both 115-134.9 kg and 135-154.9 kg showing increases in incidence of
approximately 50% over the 10-year period. Overall, obesity incidence rates have increased
modestly, with higher levels of growth occurring in the more extreme class II and III,
particularly in the jurisdictions grouped as ‘Other.’
Demographic Characteristics
Available data from CIHI’s CCRS dataset allowed for an analysis of basic demographic
features including age, sex, primary language, and place of residence prior to entry into LTC.
Comparing the demographics of persons newly residing in a LTCF through a lens of BMI
provides a descriptive profile not only of those with and without obesity, but also each BMI
class. The profile offered here is based upon an amalgamation of the consecutive cross-sectional
initial assessment data entered over a 10-year period (2010-2020) and provides an explorative
description of persons initially transitioning into CIHI-participating LTCFs.
Age Distribution
Of all individuals entering LTCFs between 2010-2020, over two thirds of the population
were 80 years of age or older (68%, n=238,636), with nearly 90% aged 70 years or older
(n=310,167). A third of persons newly residing in a LTCF aged 69 years or younger had obesity

55
(n=12,524), while only 25% aged 70-79 (n=17,845) and 15% aged 80 years and older
(n=36,139) had obesity. Figure 10 displays the age distribution seen in each of the BMI
categories. When factoring in BMI categories, there was an inverse relation between age at entry
into LTC and the presence for obesity. Nearly half of the individuals classified as obese entering
LTC were under the age of 80 (46%, n=30,369), while only 29% of those without obesity were
under 80 (n=81,343). When examining persons newly residing in a LTCF by BMI category,
there were important differences in age distribution. Most notably, the nearly two thirds of
persons entering LTCFs with class III obesity, and half of those with class II, were under the age
of 80 (n=6,629 and n=7,370 respectively) (Figure 10).
Figure 10
Age Distribution of Persons Newly Residing in a Long-term Care Facility (N=350,348), 20102020

Body Mass Index (BMI) Category

Total 1 3
Class III

4

Class II

2

8

20

9

20

5

68
31

14

Class I 1 4

29

10

Overweight 1 3

37
50

25

7

61

21

68

Normal 1 2

6

18

73

Underweight 1 2

6

17

74

Obese

2

Non obese 1 2
0

5

12
7

27

54

19
10

bc

20

71
30

40

50

60

a

70

80

90

100

Proportion of Age Group in BMI category (%)
Age Groups

<50

50-59

60-69

70-79

80+

Note. a) a The proportion of each age group is significantly different between obese and non-obese (p≤0.001).
b) b Normal BMI (reference group) is significantly different for each age group of the BMIs overweight thru class III
(p≤0.001). c) c normal BMI (reference group) is only significantly different from underweight age group 80+ years
(p≤0.001).

56
Age Groups; In-Community and Entering Long-term Care
The available CCRS data from CIHI and CCHS data allow for a comparison of obesity
rates among the population entering LTC compared to older adults living in community settings.
While the above section looked at the age distribution of the BMI categories, age group obesity
rates needed to be utilized to compare to the in-community population. The obesity rates for the
newly entered LTC population under the age of 70 was twice that of the newly entered
population 80 years and older (Figure 11). Lytvyak, Straube, Modi, & Lee (2022) conducted a
consecutive, cross-sectional study of the Canadian Community Health Survey (CCHS) for the
cycles 2005-2017/18. Their results provide information on obesity rates specific to the age
groups but, unfortunately, there is no breakdown of BMI classes (Figure 11). Comparing LTC
and in-community obesity rates, Figure 11 shows that the rates of obesity are generally similar,
although younger individuals entering LTCFs (under 60 years old) had slightly higher rates of
obesity, while persons newly residing in a LTCF aged 70 years and older had slightly lower rates
of obesity than those residing in community settings.

57

Figure 11
Comparison of Rates of Obesity for Persons Aged 50 and Older Newly Residing in a Long-term
Care Facility (n=346,283) and Adults Aged 50 years or Older Residing in Community Settings
(n=288,547), 2009-2018

Popoulation with Obesity (%)

100

Entering Long Term Care (CY 2010-2020)
80

Canadian Community Health Survey (FY 2009/10 to 2017/18)

60
40

33

31

31

31

25

28
18

15

20
0
50-59

60-69

70-79

80+

Age Groups (Years)
Note. a) Canadian Community Health Survey Data adapted from "Trends in obesity across Canada from 2005 to
2018: a consecutive cross-sectional population-based study," by Lytvyak, E., Straube, S., Modi, R., & Lee, K. K.
(2022). CMAJ Open, 10(2), E439–E449. https://doi.org/10.9778/cmajo.20210205. b) CY= Calendar Year, FY =
Fiscal Year.

A further comparison of the obesity rates seen in the community and the newly entered
LTC population over time (2010-2020) is provided in Figure 12. The rates of obesity for both the
CCHS and the LTC populations remained fairly constant over the 10-year period, with slightly
higher rates for each age groups amongst the CCHS population.

58
Figure 12
Rates of Obesity Amongst Persons Aged 60+ Newly Residing a in Long-term Care Facility
(n=336,762) and Older Adults Aged 60+ in Community Settings, 2010-2020 (n=192,641), 20102018

Age Group and Population

Annual Population with Obesity (%)

100
90

60-69 LTC

70-79 LTC

>80 LTC

80

60-69 CCHS

70-79 CCHS

>80 CCHS

70
60
50
40
30
20
10
0
2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Year
Note. a) LTC = Newly Entered Long-term Care Residents; b) CCHS = Canadian Community Health Survey
population living in-community; c) CCHS data adapted from "Trends in obesity across Canada from 2005 to 2018: a
consecutive cross-sectional population-based study," by Lytvyak, E., Straube, S., Modi, R., & Lee, K. K. (2022).
CMAJ Open, 10(2), E439–E449. https://doi.org/10.9778/cmajo.20210205

59
Sex
The CIHI assessments included options for female, male and 'other', and did not include
information on gender identity. Only 278 individuals (0.1%) were listed under this ‘other’
option. For this reason, this research offers an analysis of the distribution of males and females
but is unable to examine gender identity. Not surprisingly, the population entering LTC between
2010-2020 was predominately female (Table 3). There were slightly higher rates of obesity
amongst females than males. Across the BMI spectrum, females were more likely to have an
underweight BMI than males, and males an overweight BMI. The sex distribution of the BMI
categories is displayed in Figure 13. Persons newly residing in a LTCF with obesity were slightly
more likely to be female. The difference in sex distribution was more apparent when the full
range of BMI categories were considered. The more extreme BMI categories were more likely to
be female (underweight and classes II and III), whereas those in the overweight category were
likely to be males (Figure 13).
Table 3
Rates of Body Mass Index (BMI) Categories by Sex of Persons Newly Residing in a Long-term
Care Facility (N=348,970), 2010-2020
BMI Category
Obesity
Non-Obese
Obese
BMI
Underweight
Normal
Overweight
Class I
Class II
Class III
Total

Sex % (n)
Males 39% (134,473)

Females 61% (214,497)

82 (111,799)
18 (23,774 )

80 (171,813)
20 (42,684)

8
43
32
12
4
2
100

13
41
26
12
5
3
100

(10,689)
(57,650)
(43,460)
(16,070)
(4,766)
(2,938)
(134,473)

(27,956)
(88,470)
(88,470)
(25,177)
(10,010)
(7,497)
(214,497)

60
Figure 13
Sex Distribution of Persons Newly Residing in a Long-term Care Facility (N=348,970), 20102020

Total Population Female (61%)

Propotion of Female Residents (%)

100
80
60
40
64a

61
20

72*
61

56*

68*

61

*

*

72*
*

0
Non Obese

Obese

Underweight Normal

Overweight

Class I

Class II

Class III

Body Mass Index (BMI)

Note. a) a Significantly different from non-obese (p≤0.001). b) * Significantly different from the reference group
(normal BMI) (p≤0.001).

Language
The CCRS dataset from CIHI provided dichotomous information on an individual's
primary language, with those using English or French (i.e., Canada's "official languages") as one
category, and those using any other language as the 'Other' category. The majority (86%,
n=302,212) of individuals entering LTC (2010-2020) spoke either English and/or French as their
primary language (Figure 14). Generally, there was little difference across BMI categories,
although those with a class III obesity were slightly more likely to speak one of the two official
languages.

61
Figure 14
Primary Language Distribution of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020

Residents with English/French
as Primary Language (%)

Total Population Speaking English/French (86%)
100
80
60
40

86

88a

Non Obese

Obese

85*

86

86

87*

88*

92*

Overweight

Class I

Class II

Class III

20
0
Underweight Normal

Body Mass Index (BMI)
Note. a) a Significantly different from non-obese (p≤0.001). b) * Significantly different from the reference group
(normal BMI) (p≤0.001).

Location of Last Residence
The CCRS dataset from CIHI included a variable that records where newly entered
individuals lived immediately prior to entering a LTCF. This is a dichotomous variable with the
categories urban or rural. Urban is defined here as Statistics Canada’s census metropolitan area
or census agglomeration area (Canadian Institute for Health Information, 2022a). The majority of
newly entered individuals (84%, n=271,427) lived in urban areas prior to entering a LTCF.
Persons newly residing in a LTCF with obesity were slightly but significantly more likely to
have resided in a rural area prior to LTC (p≤0.001) (Figure 15). BMI categories had little effect
on these distributions, although there was a modest increase in the rural share of the three obese
classes of persons newly residing in a LTCF.

62
Figure 15
Location of Last Residence of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020

Resideitns Previously Living in Rural
Area (%)

100

Total Population from a Rural Location (16%)

80
60
40
20
15

19a

Non-Obese

Obese

14*

15

17*

18*

19*

19*

Overweight

Class I

Class II

Class III

0
Underweight Normal

Body Mass Index (BMI)

Note. a) a Significantly different from non-obese (p≤0.001). b) * Significantly different from the reference group
(normal BMI) (p≤0.001).

Location of Last Residence by Province/Territory
Since rural living is greatly influenced by what part of the country one resides, a further
look at how rural living played out at the provincial or territorial level was undertaken.
Provincial comparisons with Alberta should be done with caution as 30% of individuals entering
Albertan LTC were listed as having an 'unknown' previous location (n=15,098); compared with
between 3-7% in the other provincial/territorial groups (total number of unknown, including
Alberta, n=26,914). Only those individuals with a known location of last residence were included
in the analysis presented in Table 4 (N=323,434).
There were provincial discrepancies between provinces, with Alberta and the
geographical category ‘Other’ (i.e., Manitoba, Newfoundland and Labrador, Nova Scotia,
Saskatchewan, the Yukon) having over double the proportion of individuals from a rural area

63
compared to BC and Ontario. All the provinces and the ‘Other’ group reported significantly
higher rates of rural living amongst their persons residing in a LTCF with obesity (p≤0.001). BC
and Ontario exhibited very minor difference across the BMI categories. Alberta and the ‘Other’
group, meanwhile, both saw wider ranges of rural living between the BMI categories with
greater rates of rural living amongst those with an overweight or higher BMI.
Table 4
Location of Last Residence of Persons Newly Residing in a Long-term Care Facility by Province
(N=340,358), 2010-2020
Province
Non-obese
Obese
Total Population
p-value
a
(81%,
n=283840)
(19%,
n=66508)
(% Rural )
%
(n)
%
(n)
%
(n)
(df=1)
Alberta
British
Columbia
Ontario

26

(8,960)

24

(6,876)

32

(2,084)

<0.001

11

(5,075)

10

(4,223)

13

(852)

<0.001

14

(28,860)

15

(22,409)

14

(6,451)

<0.001

‘Other’b

28

(9,112)

27

(6,977)

32

(2,135)

<0.001

Underweight

Normal

Overweight

11% (38,671) 42% (146,224) 28% (98,945)

Class I
Class II
Class III
12% (41,279) 4% (14,789) 3% (10,440)

%

%

(n)

%

(n)

%

(n)

(n)

%

(n)

%

(n)

Alberta
British
Columbia
Ontario

20* (842)00 23 (3,413)00 28* (1,410)00 31* (1,250)00 34* (494)00 31* (340)00

‘Other’b

9 (584)

10 (2,229)

13* (546)

14* (181)

12* (2,583) 13 (11,096) 15* (8,730)

16* (3,959)

16* (1,488) 15* (1,004)

24 (813)

30* (1,247)

35* (507)

25 (3,358)

11* (1,410)

29* (2,806)

13* (125)

35* (381)

Note. a) a Rural defined as outside of Statistics' Canada census metropolitan area or census agglomeration area. b) b
‘Other’ composed of Manitoba, Newfoundland and Labrador, Nova Scotia, Saskatchewan and Yukon Facilities. c) *
Significantly different from the reference group (normal BMI) (p≤0.001).

64
Summary of Demographic Profile
A demographic profile was developed from the preceding analysis of the consecutive,
cross-sectional data of the population entering long-term care facilities (LTCFs) between 20102020. Over the ten-year period, people with obesity were most notably entering at a younger age
than those without obesity (p≤0.001). Persons newly residing in a LTCF with obesity were also
slightly but significantly more likely to be female, speak English/French as a primary language,
and have previously lived in a rural area (p≤0.001). When breaking the 'obese' population into
the three BMI categories, these trends became more apparent.
Health Status
The CCRS dataset from CIHI included variables for many different chronic and acute
conditions, symptoms, and health indicators. The relationship of obesity and the presence of
chronic conditions amongst long-term care persons residing in a LTCF has been looked at in
other countries, with higher rates of certain conditions (e.g., diabetes), and lower rates of others
(e.g., dementia) being noted (Ankuda et al., 2017; Cai et al., 2013). Chronic conditions, such as
diabetes and dementia, have different influences over the need for LTC, and require different
types of services and care for management while in LTCFs (Canadian Institute for Health
Information, 2014; Desai et al., 2004; Munshi et al., 2016; Nunez, 2021). To develop a broad
understanding of the health status of persons newly residing in a LTCF in relation to obesity and
BMI levels, this analysis describes the presences of the most common chronic conditions,
including an analysis of multiple chronic conditions and dyads of conditions.
Chronic Health Conditions
The CCRS dataset from CIHI included information about chronic health conditions
which allowed for calculation of rates. Chronic health conditions listed in were present in at least

65
20% of the total newly entered population or amongst 20% of individuals within a specific BMI
category. An unabridged version of Table 5 (all conditions) is provided in the Appendices 1-2.
Conditions are noted that have higher or lower rates amongst those with obesity and its classes,
and conditions are also described as having a positive, negative, or no relationship with
increasing BMI.
The most prominent conditions in the population as a whole were hypertension (i.e., high
blood pressure) (61%, n=212,511), dementia/Alzheimer’s (referred to as dementia herein) (54%,
n=190,415), arthritis (35%, n=123,708), diabetes (26%, n=91,809), osteoporosis (22%,
n=76,020) and depression (22%, n=75,829) (Table5). The proportions of most conditions shifted
with the introduction of BMI categories. Hypertension remained the most common condition in
every BMI category. For those with an underweight BMI, however, the prevalence of dementia
was the same as hypertension.
Persons newly residing in a LTCF with obesity had notably significantly higher rates of
diabetes (39% vs 23%), arthritis (42% vs 34%), hypertension (66% vs 59%), and congestive
heart failure (CHF) (20% vs 14%), and significantly lower rates of dementia (44%, 57%) and
osteoporosis (16% vs 23%) (Table 5). To a lesser extent, but still significant, those with obesity
also had higher rates of allergies, depression, emphysema/ chronic obstructive pulmonary
disease (COPD), and hypothyroidism, and lower rates of cerebrovascular accident (i.e., stroke)
(p≤0.001). These differences became more apparent when examined across all BMI categories.
Conditions that were positively associated with an increasing BMI were diabetes,
congestive heart failure (CHF), and arthritis. Diabetes exhibited the most dramatic difference by
BMI category of any condition, where 41-44% of individuals with any level of obesity had
diabetes compared to 22% of those with a normal BMI. Conditions that were not positively

66
associated across all BMI categories, but rather were positively associated only with increasing
levels of obesity, were allergies, emphysema/COPD, and depression.
Osteoporosis was the only condition with a negative association across all BMIs, with
double the rates in the underweight category as compared to those with class II or III obesity.
Dementia, meanwhile, did not have a direct relationship with every BMI category, and was
significantly less prevalent in each of the classes of obesity. Finally, stroke was not associated
directly with BMI, and the lowest rates were seen amongst those with class III obesity.
Table 5
Chronic Health Conditions of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020
Chronic Health
Condition

Total Population
% (n)
100% (350,348)

< or > 30 kg/m2 %(n)
< 30 kg/m2
81% (283,840)

≥ 30 kg/m2
19% (66,508)

p-value

%

n

%

n

%

n

(df=1)

Hypertension
Dementia and/or
Alzheimer's
Arthritis

61

(212,511)

59

(168,520)

66

(43,991)

<0.001

54

(190,415)

57

(161,348)

44

(29,067)

<0.001

35

(123,708)

34

(95,848)

42

(27,860)

<0.001

Diabetes mellitus

26

(91,809)

23

(65,673)

39

(26,136)

<0.001

Osteoporosis

22

(76,020)

23

(65,386)

16

(10,634)

<0.001

Depression

22

(75,829)

21

(58,958)

25

(16,871)

<0.001

Allergies
Cerebrovascular
accident (stroke)
Hypothyroidism

20

(74,659)

19

(53,709)

23

(15,580)

<0.001

19

(65,116)

19

(53,099)

18

(12,017)

<0.001

17

(59,677)

17

(47,257)

19

(12,420)

<0.001

Emphysema/ COPD
Congestive heart
failure

16

(56,617)

16

(44,344)

19

(12,273)

<0.001

15

(51,277)

14

(38,216)

20

(13,061)

<0.001

67
Body Mass Index (BMI) Categories % (n)
Underweight Normal
Overweight Class I
Class II
11% (38,671) 42% (146,224) 28% (98,945) 12% (41,279) 4% (14,789)

Class III
3% (10,440)

%

%

(n)

%

(n)

%

(n)

%

(n)

%

(n)

(n)

Hypertension
Dementia and/or
Alzheimer's
Arthritis

54 (20,757)00 59 (85,858)00 63 (61,905)00 66 (27,072)00 66 (10,010)00 66 (6,909)00

*

*

*

*

*

54* (20,976)

58 (85,139)

56* (55,233)

49* (20,389)

27* (5,827)

27* (2,851)

31* (11,799)

33 (48,172)

36* (35,877)

41* (16,790)

44* (6,489)

44* (4,581)

Diabetes mellitus

15* (5,740)

22 (31,586)

29* (28,347)

36* (14,732)

48* (6,442)

48* (4,962)

Osteoporosis

31* (12,153)

24 (34,640)

19* (18,593)

17* (6,935)

14* (2,250)

14* (1,449)

Depression

20 (7,754)

20 (29,657)

22* (21,547)

24* (9,903)

29* (3,939)

29* (3,029)

Allergies
Cerebrovascular
accident (stroke)
Hypothyroidism

19 (7,245)

18 (26,953)

20* (19,511)

22* (9,012)

28* (3,675)

28* (2,893)

16* (6,236)

19 (27,402)

20* (19,461)

19 (7,871)

15* (2,610)

15* (1,536)

17 (6,390)

17 (24,227)

17 (16,640)

18* (7,386)

20* (2,913)

20* (2,121)

Emphysema/ COPD 22* (8,356)
Congestive heart
12 (4,732)
failure

15 (21,960)

14* (14,028)

17* (6,913)

23* (2,967)

23* (2,393)

13 (18,921)

15* (14,574)

18* (7,441)

23* (3,183)

23* (2,437)

Note. a) a Significantly different from non-obese (p≤0.001). b) * Significantly different from the reference group
(normal BMI) (p≤0.001).

Multiple Chronic Health Conditions
Multiple chronic conditions were considered utilizing a list developed using Statistics
Canada surveys regarding chronic conditions (SAHCPDP and CSEPHC) and other literature, as
described in Chapter 3 (Methods). The vast majority (n=301,314), or 86%, of newly entered
individuals had two or more conditions (Error! Reference source not found.). Persons newly
residing in a LTCF with obesity were marginally more likely to have multiple conditions (two+
conditions). When comparing rates across BMI categories, there was little difference, although
those with classes I, II and III obesity were more likely to report 3 or more conditions.

68

Body Mass Index (BMI)

Figure 16
Multiple Chronic Health Conditions of Persons Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020
Class III

3

10*

18*

Class II

3

9*

17*

Class I

3

9*

19*

Overweight

3

11*

20*

Normal

3

12

21

25

20

19

Underweight

4

12

21

25

19

19

Obese

3

9*

Non Obese

3

11

21

25

20

20

Total

3

11

20

25

20

21

0

24*
23*
25*

19a

20

21

24*

22*

26*

21*

25

23*

20

24a

21a

21*

24a

40
60
80
Has the Number of Chronic Conditions (% Yes)
0 Conditions

1

2

3

4

100

5+ Conditions

Note. a) a Significantly different from non-obese (p≤0.001). b) * Significantly different from the reference group
(Normal BMI) (p≤0.001) b) conditions considered: Hypertension, Dementia/Alzheimer's (combined), Arthritis,
Diabetes Mellitus, Osteoporosis, Depression, Stroke, Heart disease (a combination of Arteriosclerotic heart disease
(ASHD), Congestive Heart Failure, and 'Other Cardiovascular disease'), Emphysema/COPD, Anemia, Cancer,
Asthma, Liver Disease, Hip Fracture.

Multi-Morbidities Over Time
A comparison of the incidences of multi-morbidities showed no notable significant
changes over the 10-year period (2010-2020) in any BMI category. These results are provided in
Appendix 7.

69
Dyads of Chronic Conditions
While the CCRS dataset from CIHI did not allow for an analysis of severity of disease
progression or length of time with diagnosis, it did allow for a count of the most common dyads.
A dyad refers to having two conditions simultaneously. Having multiple chronic conditions has
wide ranging implications for treatment, health management and outcome prognoses. A CIHI
(2011) study of older adults (>65 years) living in-community, based on Statistics Canada's 2008
Canadian Survey of Experiences With Primary Healthcare (CSEPHC), provides information
rates of having multiple conditions and the most common dyads for that population (Canadian
Institute for Health Information, 2011). The top five dyads of the population entering LTC are
summarized in Table 6, alongside information from that CIHI report. A limitation of this
comparison is that the index utilized by the CSEPHC did not include dementia, a common
chronic condition in the LTC population (Canadian Institute for Health Information, 2011).
The overall prevalence of dyads in general were higher amongst persons newly residing
in a LTCF , as compared to older adults living in community (Canadian Institute for Health
Information, 2011) (Table 6). This is to be expected, as the population entering LTC represents
those whose health has declined to the point of needing more intensive care. Excluding dementia,
the most common dyads in both populations were [hypertension-arthritis] (LTC 24%, incommunity 14%), [hypertension-heart disease] (23%, 12%), and [hypertension diabetes] (19%,
11%).
The relationship between dyads and BMI status amongst the newly entered LTC
population was apparent in some dyads and not others. Dyads containing any combination of
dementia, diabetes or osteoporosis showed the most sensitivity to BMIs. Two of the dyads seen
in the highest frequencies in the in-community population and LTC population ([hypertension-

70
arthritis] and [hypertension-heart disease]) remained in the top five dyads regardless of BMI, and
the rates of both dyads exhibited a positive relationship with increasing BMI. Since LTC dyads
include dementia, [hypertension-dementia] is the most common dyad amongst persons newly
residing in a LTCF, present in both a third of the total LTC population and the population
without obesity. However, [hypertension-dementia] occurred at lower rates and was tied with
[hypertension-diabetes] for second most common dyad for those with obesity (29%). Likewise,
across the BMI categories, [hypertension-dementia] was the most prevalent dyad for all those
with a BMI under class II obesity, while the most prevalent dyad among those with classes II and
III obesity was [hypertension-diabetes]. Diabetes only appeared in the highest BMI categories,
while osteoporosis was seen only in the underweight category, and dementia does not appear in
the top five dyads of persons residing in a LTCF with class III obesity.
Managing multiple chronic conditions is a common occurrence in LTCFs. When
compared to older adults living in community settings, persons newly residing in a LTCF had a
higher frequency of dyads, and the dyad pairings appear to be affected by BMI. That said,
hypertension, heart disease, and arthritis were common in various dyads regardless of BMI. The
BMI dependent conditions included osteoporosis amongst the underweight, dementia for those
without obesity, and diabetes for those with obesity.

71
Table 6
Top Five Dyads of Chronic Health Conditions of Persons Newly Residing in a Long-term Care
Facility, 2010-2020 (n=350,348), and In-Community Adults Over 65 for the Year 2008
(n=3,132)
Top five dyads of those entering LTC 20102020
Hypertension and Dementia (33%)
Hypertension and Arthritis (24%)
Hypertension and Heart Disease (23%)
Arthritis and Dementia (19%)
Hypertension and Diabetes (19%)

Top five dyads from in-community older
adultsb
High blood pressure and arthritis (14%);
High blood pressure and heart disease (12%);
High blood pressure and diabetes (11%);
Heart disease and arthritis (6%); and
High blood pressure and cancer (6%).

Top five dyads of those entering LTC 2010-2020, by Body Mass Index
Without Obesity

With Obesity

Hypertension and Dementia (34%)
Hypertension and Arthritis (22%)
Hypertension and Heart Disease (22%)
Arthritis and Dementia (19%)
Hypertension and Diabetes (18%)

Hypertension and Arthritis (30%)
Hypertension and Diabetes (29%)
Hypertension and Dementia (29%)
Hypertension and Heart Disease (28%)
Arthritis and Dementia (19%)

Underweight

Normal

Overweight

HT & Dementia (30%)
HT & Osteoporosis (18%)
HT & Heart Disease (18%)
HT & Arthritis (18%)
Dementia & Osteoporosis
(18%)

HT & Dementia (34%)
HT & Heart Disease (21%)
HT & Arthritis (21%)
Arthritis & Dementia (19%)
Heart Disease & Dementia
(18%)

HT & Dementia (35%)
HT & Arthritis (25%)
HT & Heart Disease (24%)
Arthritis & Dementia (21%)
Heart Disease & Dementia
(20%)

Class I

Class II

Class III

HT & Dementia (32%)
HT & Arthritis (29%)
HT & Heart Disease (27%)
HT & Diabetes (27%)
Arthritis & Dementia (20%)

HT & Diabetes (35%)
HT & Arthritis (32%)
HT & Heart Disease (30%)
HT & Dementia (27%)
Heart Disease & Diabetes
(20%)

HT & Diabetes (35%)
HT & Arthritis (32%)
HT & Heart Disease (29%)
Heart Disease & Diabetes
(22%)
Arthritis & Diabetes (21%)

Note. a) LTC - Canadian Institute for Health Information Participating Long-Term Care Facilities. b) Adapted from:
Canadian Institute for Health Information. (2011). Seniors and the Healthcare System: What Is the Impact of
Multiple Chronic Conditions ?, (January). Retrieved from https://secure.cihi.ca/free_products/airchronic_disease_aib_en.pdf.

72
Summary of Chronic Health Conditions
Hypertension, dementia, and arthritis were present in much of the population entering
LTC between 2010-2020. Persons newly residing in a LTCF with obesity entered with higher
frequencies of all the top chronic conditions, except for having lower frequencies of dementia,
stroke, and osteoporosis. The rates for many chronic conditions varied by BMI category. The
most prominent of these were diabetes, dementia, and osteoporosis. Diabetes, chronic heart
failure (CHF) and arthritis were positively associated with increasing BMI while osteoporosis
was negatively associated with increasing BMI. Dementia rates, meanwhile, decreased with
increasing obesity. The highest BMI categories saw about half the rates of dementia and
osteoporosis and twice the frequency of diabetes as seen in the reference population. Persons
newly residing in a LTCF with obesity were more likely to have five+ conditions and the
likelihood of reporting three or more conditions increased with BMI levels. Finally, while
[hypertension-arthritis] and [hypertension-heart disease] were prominent across the BMI
categories, [hypertension-dementia] was the most common dyad for persons newly residing in a
LTCF with a BMI below class II obesity, and [hypertension-diabetes] for those with class II or
class III obesity. Overall, while dementia is present in the majority of the LTC population other
conditions, especially diabetes, appeared to be more prevalent for the populations with higher
BMIs.
Activities of Daily Living (ADLs)
The ability to perform activities of daily living (ADLs), and the level of support needed
for persons newly residing in a LTCF to perform these activities, are included in the initial
assessments, and assessed herein. The ability to perform ADLs, along with changes in
performance abilities, provide information on overall health status and autonomy of persons

73
residing in LTCFs (Canadian Institute for Health Information, n.d.). Research on older adults
with obesity living in institutions have highlighted the impact obesity has on ADL performance,
including the greater need for two+ person assistance when performing the ADLs (Harris et al.,
2018), and being able to perform certain ADLs at a higher level of independence, while
sometime performing other worse (Amankwaa et al., 2022; Bahat et al., 2012; Kiesswetter et al.,
2014). For simplification, this research examines those requiring two+ person physical
assistance, and those whose self-performance was assessed as 'independent'. Two+ person
physical assistance was chosen as this more resource intensive level of assistance has been
explored in previous literature surrounding individuals with obesity in long-term care settings
(Harris et al., 2018; Kosar et al., 2018; Zhang, Field, et al., 2019). Independent self-performance
represents individuals who require the least amount of assistance and have the highest level of
functioning. The results are stratified by the presence or not of a dementia diagnosis. This was
done to provide an estimate of the level of cognitive impairment that would affect independent
self-performance of ADLs. It is important to note that there is a high likelihood that dementia is
underdiagnosed (Parker et al., 2020), thus underestimating the level of cognitive impairment
present in the population studied. All the values of assistance provided, and self performance are
provided in Appendices 3-6.
Two+ Person Assistance
For all persons newly residing in a LTCF there was little to no requirement for two+
person assistance for the ADL activities of eating, walking, and locomotion (≤ 4% required two+
person assistance). The remaining ADLs are displayed in Table 7. Most notably, a third of the
newly entered population required two+ person assistance with the ADLs transfer, toileting, and
bathing (Table 7). Having obesity resulted in higher rates of two+ person assistance for every

74
ADL (excluding eating, walking and locomotion), but the differences, while significant
(p≤0.001), were not large (≤4% difference). There were greater differences in needing two+
person assistance across the BMI categories, with ADLs seeing max ranges in proportions of 813%. The normal, overweight and class I obese groups have very similar levels of needing two+
person assistance. While those with underweight BMI required slightly more assistance than the
three middle BMIs (i.e., normal, overweight, class I obese), those with class II and class III
obesity were most likely to require two+ person assistance. The similarities between the three
middle BMI groups hides the assistance requirements of the more extreme BMIs. Overall,
having obesity resulted in higher rates of needing two+ person assistance, and need was greater
amongst those with the highest BMI.

75

Table 7
Two+ Person Assistance Required by Person Newly Residing in a Long-term Care Facility
(N=350,348), 2010-2020
Activity of
Daily Living

Total Population
(100%, N=350348)
%

(n)

Two+ Person Assist Required
Non Obese
Obese
(81%, n=283840)
(19%, n=66508)
% (n)

%

p-value
(df=1)

(n)

Dressing

19 (65,088)

18 (51,212)

21 (13,876)

<0.001

Bed
Mobility

28 (97,396)

27 (76,515)

31 (20,881)

<0.001

Transfer

33 (116,654)

33 (92,466 )

36 (24,088 )

<0.001

Toileting

33 (114,877)

32 (90,993)

36 (23,884)

<0.001

Personal
Hygiene

19 (66,389)

18 (52,272)

21 (14,117)

<0.001

Bathing

30 (105,838)

30 (84,121)

33 (21,717)

<0.001

Activity of
Underweight
Normal
Overweight
Class I
Class II
Class III
Daily Living (11%, n=38,671) (42% n=146,224) (28%, n=98,945) (12%, n=41,279) (4%, n=14,789) (3%, n=10,440)
% (n)

% (n)

% (n)

% (n)

% (n)

% (n)

Dressing

19 (7,496)*

18 (26,117)

18 (17,599)

19* (7,996)

21* (3,130)

26* (2,750)

Bed
Mobility

30 (11,717)*

27 (11,717)

26 (38,775)

29* (11,940)

33* (4,824)

39* (4,117)

Transfer

37 (14,368)*

32 (14,368)

31* (47,237)

34 (14,005)

38* (5,577)

43* (4,506)

Toileting

35 (13,650)*

32 (13,650)

31 (46,491)

34* (14,030)

37* (5,422)

42* (4,432)

Personal
Hygiene

20 (7,578)*

18 (7,578)

18 (26,730)

20* (8,105)

22* (3,211)

27* (2,801)

Bathing

31 (12,077)*

29 (12,077)

29 (42,997)

31* (12,852)

33* (4,928)

38* (3,937)

Note. a) * Significantly different from the reference group (normal BMI) (p≤0.001).

76
Self Performance of Activities of Daily Living (ADLs)
The analysis reported in Table 8 stratifies persons newly residing in a LTCF by dementia
status and finds an inverse relation between rates of dementia and obesity.
Table 8
Stratified Frequencies of Dementia and Body Mass Index for Person Newly Residing in a Longterm Care Facility (N=350,348), 2010-2020
Body Mass
Index (BMI)

Not Stratified

With Dementia

Without Dementia

p-value

% (n)

% (n)

% (n)

(df=1)

Obesity
Non-Obese
Obese
BMI Category

81 (283,840)
19 (66,508)

85 (161,348)
15 (29,067)

77 (122,492)
23 (37,441)

<0.001
<0.001

Underweight
Normal
Overweight
Class I
Class II
Class III
Total

11
42
28
12
4
3
100

11
45
29
11
3
2
54

11
38
27
13
6
5
45

0.651
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001

(38,671)
(146,224)
(98,945)
(41,279)
(14,789)
(10,440)
(350,348)

(20,976)
(85,139)
(55,233)
(20,389)
(5,827)
(2,851)
(190,415)

(17,695)
(61,085)
(43,712)
(20,890)
(8,962)
(7,589)
(159,933)

Note. * Significantly higher proportion between those with and without dementia (p≤0.001).

Proportional Ratios
The proportions of persons newly residing in a LTCF operating at a level considered
independent when performing the activities of daily living (ADLs) are provided in Table 9 and
Table 10. Figure 17 uses proportional ratios (PRs) to compare the ADL independence rates of
those with and without obesity, while Figure 18 compare BMI categories to those with a
‘normal’ BMI (i.e., the reference group chosen for this analysis). The added layer of stratifying
by dementia results in two proportional ratios (PRs) for each ADL and these results are
contained to their dementia stratified group. The two PRs for each ADL are presented in such a

77
way as to allow for a visual representation of the results in Figures 17 and 18 (refer to Chapter 3,
Methods).
ADL Independence as Stratified by Dementia and Obesity
Before stratifying by dementia, those with obesity had significantly higher levels of
independence for eating, and both locomotion on and off unit, with minor differences in other
ADLs (p≤0.001) (Table 9), "Not Stratified"). These associations persisted even when stratified
by dementia status. Regardless of obesity status, having dementia resulted in lower rates of
independence in eating, dressing, hygiene, and locomotion off unit (Table 9). However, the
negative impact of dementia was less apparent in the independence for the activities of bed
mobility, transfer, walking in room, and walking in corridor, again regardless of obesity status.
The conditions other than dementia (without dementia group) appeared to be associated with
higher independence for more intricate ADLs or for leaving the unit but was associated with
lower independence with less intricate skills and mobility on unit (Table 9). Further analysis of
these proportions of independence and their relation to obesity are considered in Figure 17 using
proportional ratios.

78
Table 9
Independence of Activities of Daily Living (ADLs) for Person Newly Residing in a Long-term
Care Facility (N=350,348), 2010-2020
Activity of Daily
Living
(Independent)

Population Stratified by Dementia and Obesity status
Not Stratified
(100%, N=350,348)
Non-obese

Obese

With Dementia
(54% n=190,415)
Non-obese

Obese

Without Dementia
(46%. n=159,933)
Non-obese

Obese

(81% n=283,840) (19% n=66,508) (85%, n=161,348) (15%, n=29,067) (77%, n=122,492) (23%, n=37,441)

% (n)

% (n)

% (n)

% (n)

% (n)

% (n)

Eating
Dressing

33 (93,823)
8 (22,038)

40* (26,542)
8 (5,544)

30 (48,029)
7 (10,873)

35* (10,081)
7 (2,038)

37 (45,794)
9 (11,165)

44* (16,461)
9 (3,506)

Bed Mobility
Transfer
Locomotion
On Unit
Locomotion
Off Unit
Walk in
Room
Walk in
Corridor
Toileting
Hygiene
Bathing

32 (90,220)
26 (64,823)

30* (20,244)
25* (14,639)

34 (54,371)
26 (41,955)

34 (9,957)
27 (7,825)

29 (35,849)
19 (22,868)

27* (10,287)
18 (6,814)

26 (75,136)

30* (19,724)

27 (42,980)

29* (8,415)

26 (32,156)

30* (11,309)

16 (44,953)

20* (13,239)

14 (22,409)

16* (4,637)

18 (22,544)

23* (8,602)

27 (77,895)

27* (17,854)

31 (50,786)

34* (9,837)

22 (27,109)

21 (8,017)

23 (65,311)
14 (38,990)
8 (20,996)
1 (2,957)

22* (14,905)
14 (9,348)
7* (5,730)
1 (812)

26 (42,748)
14 (21,948)
6 (9,234)
1 (1,446)

28* (8,263)
14 (4,153)
6 (1,764)
1 (302)

18 (22,563)
14 (17,042)
10 (11,762)
1 (1,511)

18 (6,642)
14 (5,195)
11* (3,966)
1 (510)

Note: *Significantly different proportion from non-obese of same dementia status (p ≤0.001).

The proportional ratios (PR) comparing the proportions of independence between those
with and without obesity are displayed in Figure 17. Eating, locomotion on unit and locomotion
off unit were the only ADLs to have significantly higher rates of independence for those with
obesity, regardless of dementia status (p≤0.001). Dementia did not appear to influence
independence PRs for eating however dementia resulted in smaller PRs for locomotion on and
off unit (i.e., the 'benefit' of obesity for independence of these ADLs was greater amongst those

79
without dementia). While there were significant differences in bed mobility, walk in room, walk
in corridor and hygiene, the effects of these were small (p≤0.001).
Figure 17
Proportional Ratios of Obesity Status for Independence in Activities of Daily Living of Persons
Newly Residing in a Long-term Care Facility (N=350,348), 2010-2020

Note. a) * Significant difference between non-obese and obese groups with dementia (p≤0.001).
^ Significant difference between non-obese and obese groups without dementia (p≤0.001).
b) A proportional ratio of 1 shows an equal independence ratio, > 1.0 shows higher independence for those with
obesity, and <1.0 shows lower independence for those with obesity.

80
ADL Independence Level of Reference Group (Normal BMI)
The proportional ratios for underweight, overweight, class I, class II and class III were
calculated relative to those with a normal BMI (i.e., the reference category). Values of
independence for the reference group are provided in Table 10, while the values of independence
for the remaining 'non-normal' BMIs are provided in Appendix 8. When comparing the normal
BMI group by dementia status, having dementia was associated with significantly lower
likelihood of independence when performing the tasks of eating, dressing, locomotion off unit,
and personal hygiene and a significantly higher likely to be independent for bed mobility,
transfer, walking in room, and walking in corridor (Table 10) (p≤0.001).
Table 10
Independence of Activities of Daily Living, for Person Newly Residing in a Long-term Care
Facility with a Normal Body Mass Index (N=146,224), 2010-2020
Activity of Daily
Living

Eating
Dressing
Bed Mobility
Transfer
Locomotion on Unit
Locomotion off Unit
Walking In Room
Walking In Corridor
Toileting
Personal hygiene
Bathing

Dementia Status (N)
Not Stratified
(N=146,224)
%
(n)
32 (47,200)
8 (11,249)
32 (46,711)
23 (33,528)
26 (38,403)
16 (22,687)
28 (40,238)
23 (33,655)
14 (19,923)
7 (10,601)
1 (1,464)

With Dementia
(58%, n=85,139)
%
(n)
29 (24,842)
7 (57,73)
34 (28,761)
26 (22,170)
26 (22,511)
14 (11,654)
31 (26,648)
26 (22,363)
14 (11,561)
6 (48,97)
1 (752)

Without Dementia
(42%, n=61,085)
%
(n)
37 (22,358)
9 (5,476)
29 (17,950)
19 (11,358)
26 (15,892)
18 (11,033)
22 (13,590)
18 (11,292)
14 (8,362)
9 (5,704)
1 (712)

p-value
(df=1)
<0.001
<0.001
<0.001
<0.001
0.069
<0.001
<0.001
<0.001
0.545
<0.001
<0.001

The results for those with an underweight BMI (Figure 18(i)) show clear differences in
independence, where, regardless of dementia status, having an underweight BMI resulted in

81
significantly lower independence (PRs <1.0, p≤0.001). The second consideration of PRs shows
that having dementia appeared to exacerbate the impact underweight BMI had on ADL
independence, resulting in lower proportion of independence for those with an underweight BMI
and also dementia (x PRs < o PRs). This impact of dementia appeared most exaggerated for bed
mobility. Overall, having an underweight BMI resulted in lower ADL performances, which were
further stressed by having dementia and underweight together, and it was especially noticeable in
bed mobility.
The result for those with an overweight BMI (Figure 18(ii)) reveal consistently
significantly higher rates of independence amongst those with an overweight BMI, regardless of
dementia status, with the exceptions of dressing, hygiene and bed mobility. Dressing and hygiene
saw significantly higher rates of independence only amongst those without dementia and bed
mobility had higher rates only for those with dementia (p≤0.001). Overall, dementia status
seemed to have only minor impacts on most ADLs (short line between x and o), however the
difference was notable in dressing and hygiene. While an overweight BMI was associated with
higher rates of independence in most ADLs, this was not seen for dressing and hygiene.
Class I obesity results (Figure 18(iii)) show more similarities to the reference group than
seen in the overweight graph. Regardless of dementia status, having class I obesity was
associated with higher rates of independence for the ADLs of eating, locomotion on unit, and
locomotion off unit. For those without dementia, having class I obesity also resulted in
significantly higher independence rates for hygiene. Meanwhile, those with dementia and class I
obesity saw significantly higher rates of independence for bed mobility, transfer, and both
walking in room and corridor (p≤0.001). Persons newly residing in a LTCF with dementia and

82
class I obesity outperformed in twice as many ADLs as compared to the class I obesity group
without dementia.
Persons newly residing in a LTCF with class II obesity were the most similar to the
reference groups, regardless of dementia status (Figure 18(iv)). There were only two ADLs,
eating and locomotion off unit in which those with dementia and class II obesity had
significantly higher rates than their normal BMI counterparts with dementia. Meanwhile those
without dementia also had significantly higher rates of independence for eating, and locomotion
off unit, but also locomotion on unit and bed mobility. Stratifying by dementia status did not
appear to impact the independence proportional ratios of eating or bed mobility, however it
resulted in lower PRs for locomotion on and more so locomotion off unit.
Finally, persons newly residing in a LTCF with dementia but with a class III BMI had
significantly higher rates of independence in eating, but otherwise were similar to the reference
group without dementia (p≤0.001) (Figure 18(v)). Persons newly residing in a LTCF without
dementia however saw significantly different rates of independence for most ADLs, both higher
and lower. Eating, locomotion and off unit had significantly higher rates of independence for
those with class III, while bed mobility, transfer, walk in room, and walk in corridor were
significantly lower. The impact of dementia was greatest for walk in corridor and walk in room,
followed by locomotion on unit and off unit.

83
Figure 18
Proportional Ratios of Body Mass Index Categories of Independence of Activities of Daily Living
for Persons Newly Residing in a Long-term Care Facility (N=350,348), 2010-2020

i.

ii.

84
Figure 18 (Continued).

iii.

iv.

85
Figure 18 (Continued).

v.

Note. a) * Significant difference between 'the BMI in the title' and normal BMI p ≤ 0.001 for those with
dementia (x). ^ Significant difference between 'the BMI in the title' and normal BMI p ≤ 0.001 for those
without dementia (o). b) A proportional ratio of 1 shows an equal independence ratio, > 1.0 shows higher
independence over the reference group, and <1.0 shows lower independence than the reference group.

Summary of Self Performance of Activities of Daily Living (ADLs)
There was a relationship between the ability to perform certain activities of daily living
(ADLs) independently and an individual's dementia status and their Body Mass Index (BMI).
Overall, regardless of dementia status, having an overweight or class I obesity was associated
with better independence in most ADLs. The ADLs of eating, locomotion on unit and
locomotion off unit were most consistently showed greater rates of independence across all

86
BMIs above normal weight. Meanwhile class II obesity, with and without dementia, and class III
obesity with dementia had more in common than differences with the normal BMI group. The
underweight group had the lowest rates of independence. Finally, while dementia resulted in
lower independence for many of the ADLs, especially in the underweight, the difference in PR
were often minor, and for class III obesity having dementia resulted in higher PRs.
Overall, the data indicated an association between the BMI status of persons newly
residing in a LTCF and their ADL performance. The data also suggested that the presence of
dementia influenced the impact of BMI on self performance. Regardless of dementia status,
persons newly residing in a LTCF with an underweight BMI had lower independence, while
those with an overweight or class I obesity appear to perform ADLs more independently.
Summary of Results
The incidence of obesity amongst individuals entering Canadian long-term care increased
incrementally over the last 10 years (2010-2020). There were notable differences in
provincial/territorial LTC obesity levels and rates of increase in these, although increases in
obesity rates were observed in all geographical categories. The overall incidence of obesity was
comparable to the prevalence of obesity amongst the in-community Canadian population aged
80+ (2010-2018). Obesity rates among persons newly residing in a LTCF declined sharply with
age, although these patterns are also consistent with those observed among the population of
older adults living in community settings. Likewise, levels of obesity were typically higher
among persons newly residing in a LTCF from rural areas, but this is in line with generally
higher rates of obesity among older rural individuals more generally. Finally, obesity rates did
not differ much by sex or primary language.

87
Health conditions such as hypertension permeated the LTC population regardless of BMI,
however dementia, congestive heart failure, osteoporosis and diabetes had connections to BMI.
Those with obesity were more likely to have diabetes and congestive heart failure and less likely
to have dementia or osteoporosis. People with obesity generally, and with increasing levels of
obese BMI, were more likely to have increasing numbers of chronic conditions when entering
LTC. The combinations of these conditions showed that hypertension, heart disease, and arthritis
were in the top five dyads of every BMI category, however diabetes was far more prominent
amongst those with the heaviest BMIs. Persons with obesity were also more likely to requires
two+ person assistance in their ADLs. Finally, having an overweight or class I BMI was
associated with greater independence of ADLs. As BMI increased to class II and III obesity, this
association decreased, especially for those without dementia.
Overall, the data suggested that the populations entering LTC with a normal BMI,
overweight BMI or class I obese BMI were more similar than different in their demographics,
health conditions and ADL functioning. The more extreme BMIs of underweight, class II obesity
and class III obesity exhibited more chronic health conditions, and required more two+ person
assistance, but had better ADL functioning for eating, and locomotion-based tasks. These
differences were often masked when utilizing the arguably arbitrary grouping of obese and nonobese individuals.

88
Chapter Five: Discussion
Canadian long-term care facilities (LTCFs) are on the cusp of a population shift. As baby
boomers enter retirement and later retirement years, there is a projected large increase in the
demand for LTC and other health services utilized by an older population (Banerjee, 2007;
Estabrooks et al., 2020; Roblin et al., 2022). Monitoring the initial wave of baby boomers
entering long-term care (LTC) provides insights about potential changes in future LTC
populations. LTC is seen as more expensive in comparison to other alternatives such as at-home
aging services or facilities for lower care needs (Bender & Holyoke, 2018; Haber, 2016), and
staying out of LTC is generally preferred by older adults (Leroux et al., 2021; Weeks et al.,
2021; Westwood, 2016). One strategy in meeting this increase in demand is to delay entrance
into LTC, which can have financial and system capacity benefits (Canadian Institute for Health
Information, 2017c). Understanding the population entering into LTC will therefore provide
direction for programs aimed at delaying or preventing the transition into LTC (Canadian
Institute for Health Information, 2020a).
Alongside an aging population, obesity rates in the general Canadian population have
increased over time (Bancej et al., 2015; Lytvyak et al., 2022; Twells et al., 2014), but how this
translates into obesity rates in the Canadian LTC population has not been widely studied.
Evidence from other countries suggests that obesity is associated with a greater risk of requiring
LTC, more costly use of services in LTCFs , and a greater risk of needing specialized equipment
and two+ person assistance (Cai et al., 2013; Felix et al., 2011; Miles et al., 2012; Williamson et
al., 2023). The findings reported in this thesis suggest those with obesity represent a minority of
the population newly residing in a LTCF (19%), but that rates of obesity in this group increased
13% between 2010-2019, and those with heavier BMIs experienced an even greater increase

89
over this period. Moreover, the incidence of persons with a body weight at risk of needing costly
bariatric equipment increased by 50%. It unknown how this increase in obesity rates and risk of
bariatric equipment has impacted Canadian LTC. Although the Canadian Standards Association
does include accessibility requirements, including for bariatric equipment (Canadian Standards
Association, 2018), ensuring health equity for these individuals residing in LTCFs may be
difficult to achieve as older facilities have previously been designed for individuals with
different body types and care needs.
What Do We Know About Persons Newly Residing In LTCFs with Obesity?
Utilizing CIHI initial assessment data collected between 2010-2020 inclusive, the
findings of this research suggest that persons newly residing in a LTCF with obesity were, in
many ways, reasonably representative of the older Canadian population and the LTC population
in general, at least for many of the demographic characteristics considered. A closer examination
of the data, however, reveals a more nuanced understanding of the characteristics and needs of
this LTC sub-population.
While the majority of the LTC population is female (61%), the data suggests that females
newly admitted to LTC in Canada were disproportionately represented in the more extreme BMI
categories (i.e., classes II and III obesity and underweight, had a proportion of 68%, 72% and
72% female respectively). Previous studies in other countries reported that persons residing in a
LTCFs with obesity were more likely to be female, but these studies do not report on levels of
obesity (Cai et al., 2013; Kuchibhatla et al., 2013). Sex and gender are highly interrelated, and
while the data looks at sex specifically there is well established literature on gendered factors
related to obesity, such as survivorship rates, likelihood of living alone, and care roles, all of
which attribute to higher rates for females in LTCFs (Mudrazija et al., 2015). Gruneir, Forrester,

90
Camacho, Gill, and Bronskill, (2013), for example, found that women entered into Canadian
LTCFs at a younger age, while men presented with higher levels of needs. Obesity also carries a
gendered disparity in a variety of factors, including employment, education settings, romantic
relationships, healthcare and mental health treatment, and portrayals in the media, all of which
have a significant negative impact on health, quality of life, and socioeconomic outcomes
(Fikkan & Rothblum, 2012; Jovančević & Jović, 2022). There are also other gendered
considerations outside the men and women binary that could potentially impact an individual’s
ability or willingness to access LTC, however the CCRS dataset from CIHI was limited to only
sex. Understanding the population entering LTC will, by the nature of the demographics, require
more particular attention to the gendered processes of interpersonal relations that older females
experience, while also being aware of the intersection of gender-specific weight biases, including
internalization-biases, that older adults with obesity face.
In addition to gendered considerations, there is a need for the continued
acknowledgement and consideration for LGBTQ+ persons that face unique challenges and fears
when accessing and living in LTCFs (Fasullo et al., 2021; Hafford-Letchfield et al., 2018; Taha
et al., 2022; Villar et al., 2022; Westwood, 2016). For LGBTQ+ people with obesity, there is an
intersection of health related stigmas, resulting in higher health risks (Paine, 2021). The older
generation has seen higher rates of erasure of diverse gendered and sexual orientation identities
(Hafford-Letchfield et al., 2018; Neville & Henrickson, 2010; Statistics Canada, 2022a), which
emphasizes the need for creating space for this population in LTCFs. Future research would do
well to explore the older LGBTQ+ population experiences of living both in-community and
when accessing LTC, ensuring the inclusion of experiences of weight biases or barriers

91
encountered, such exercises will help to normalize their experiences and explore possible health
equity issues they may face.
In addition to sex differences, persons newly residing in a LTCF with obesity entered
LTC at a relatively younger age, with significantly higher proportions in every age group under
80+ (p≤0.001). Indeed, most individuals with class II or class III obesity entered LTC before the
age of 80. This is consistent with findings of previous studies looking at obesity in LTCFs in
other countries (Ankuda et al., 2017; Bradway et al., 2008; Kuchibhatla et al., 2013; Zhang et al.,
2013). There are many implications to consider when examining the health equity of a younger
LTC population. Two main considerations are the consequences of having a younger-older adult
population in LTCFs, and the reasons for transitioning into LTC at a younger age. For the first
consideration, facilities have been tailored to address the needs of an older population, including
such considerations of room temperature, dietary options, mealtimes, and scheduled activities.
Younger individuals residing in LTCFs, however, have been found to have different social,
emotional and psychological needs then their older counterparts, with the risk of depression and
social isolation when these needs are left unmet (Hay & Chaudhury, 2015; Shieu et al., 2022;
Tapley, 2018). The second aspect to consider is that the reasons a person enters LTC at a
relatively younger age may differ from those affecting older incoming persons. Entering LTC
generally means that the level of burden from an individual's health conditions outweigh the
efforts or capacities available to cope in a community or alternative setting. The findings of this
research show that entering LTC at a younger age was more likely related to complications of
diabetes, rather than dementia, and may have also been influenced by the need for more
extensive two+ person assistance, which would place a greater burden on alternative support
services.

92
An important subgroup identified in the demographic profile of persons newly residing in
a LTCF are those whose primary language is something ‘other’ than one of Canada’s two
Official Languages. In Canada, a primary language other than English or French is associated
with immigration status and ethnicity. Both characteristics have implications for older adults
with obesity in LTCFs. Not speaking English/French as a primary language increases the risk of
an incongruence of communication between persons residing in a LTCF and the facility and its
staff. An incongruence of languages may be a result of speaking an official language but not of
the location of residence (e.g., speaking French in an English part of the country), immigration
status, being from First Nations, Métis or Inuit communities, or deafness (Bowen, 2001).
Regardless of its cause, having mismatched communication languages acts a barrier in accessing
healthcare (Bowen, 2001; Pot et al., 2020) and impacts quality of care (Jeong et al., 2020; Koehn
et al., 2018; Non-communiciable Diseases Risk Factor Collaboration (NCD-RisC), 2016; Qiao,
2020; Reppas-Rindlisbacher et al., 2022). Only a small minority of those with obesity, and even
fewer with higher classes of obesity, reported speaking a primary language other than
English/French. This minority of a minority group may be facing intersecting negative factors of
weight biases (including culturally influenced weight biases) and an incongruence of language
and/or culture. Older immigrant adults living in Canadian LTCFs with obesity, especially higher
levels of obesity, may encounter barriers unlike their majority counterparts, and providing
equitable care for such a minority group would require further exploration of these experiences.
Finally, this analysis considered the influence of fairly crude indicators of urban or rural
location of residence prior to entering LTC. The findings of this analysis suggest higher rates of
obesity among those entering LTC from rural locations, with some differences observed between
the provinces and territory included in the analysis. Providing and accessing healthcare resources

93
while living in a rural setting are major challenges for the Canadian healthcare system and
people living in a rural area. Canadians in rural and smaller centers face barriers in accessing
both LTCFs and alternatives to LTC with recent findings showing that fifty percent of
individuals entering into Canadian LTCFs from rural areas could have been diverted if adequate
community care was available (Canadian Institute for Health Information, 2020a; Kuluski,
Williams, Berta, et al., 2012; Kuluski, Williams, Laporte, et al., 2012). Community care for
various programs such as dementia and diabetes were also found to be harder to access and
limited in availability in rural Canada (Camargo-Plazas et al., 2022; Morgan et al., 2015). An
individual in a rural area may face limited local availability with the nearest LTC placement
farther away than if they were in an urban center that had more options within a reasonable
distance from home. As an example, the closure of a rural LTCF with dementia specialization in
rural Alberta forced persons residing in the LTCF to transfer to urban based facilities located
hours away, negatively impacting the persons residing in the LTCF and their families
(Brassolotto et al., 2020). Obesity, like dementia, has specialized considerations for care, with
higher levels of obesity requiring facilities to have the structural capacities to handle bariatric
equipment, if a facility, such as the one in Alberta, can be closed because the health service
agency deemed it 'too costly to repair'(Brassolotto et al., 2020), than the cost of retrofitting older
buildings for bariatric use may also be 'too costly' and instead force individuals to enter into
centralized care in urban centers. It is unknown to what extent this occurs in a Canadian context
or if the problem is greater in rural areas; while Miles et al., (2012) reported that 52% of
placements of patients with obesity from hospitals in a southern American state had difficulty
placing within a "reasonable distance" from home, they were unable to determine if the problems
were greater in rural areas. There is, therefore, an intersection of barriers that may be

94
experienced, whereby having higher obesity may limit the number of LTCFs with the capacity to
accept bariatric patients, and living in a rural area means there are even more limited resources.
The resilience and resourcefulness of individuals with higher levels of obesity in rural and
smaller areas should be explored further, particularly with respect to how they manage the
barriers of a healthcare system filled with weight bias coupled with limited availability and
accessibility of LTC.
Understanding the Care Needs of Persons Newly Residing In LTCFs with Obesity
The initial assessments conducted on, or shortly after, entry to LTC offer a general
understanding of condition prevalence amongst persons newly residing in a LTCF. While the
prevalence of conditions in Canadian LTCFs are well studied (Canadian Institute for Health
Information, 2020c), this data adds to the literature as it includes differences seen in the newly
entered populations with and without obesity and across BMIs. The information highlights
differences and does not attempt to attribute obesity as the reason for the differences. In addition,
the statistical results should be treated with caution given the large number of assessments
considered. That is, a significant difference noted in a large sample does not necessarily imply
clinical significance. Rather than relying simple on statistical significance, the discussion and
results focused on the proportions with the greatest differences which may prove to be more
clinically relevant.
Dementia and diabetes are two of the major conditions in LTC populations (Canadian
Institute for Health Information, 2020c). The rates of both dementia and diabetes amongst
persons newly residing in a LTCF showed relationships with BMI levels, and these relationships
are considered below.

95
Dementia is a prominent condition appearing in 25% of the oldest Canadians and is
projected to grow in incidence as the population ages (Public Health Agency of Canada, 2017).
While the majority (61% ) of Canadians with dementia live outside of LTC, dementia is the
largest contributing factor for needing LTC (Canadian Institute for Health Information, 2023;
Halonen et al., 2019). It was, therefore, unsurprising that the newly entered LTC population had
a higher prevalence of dementia (54%) than the in-community population. The rate of dementia
was lower amongst those with obesity, and decreased with increasing BMI, reflecting previous
literature on LTC populations in other countries (Ankuda et al., 2017; Cai et al., 2013). A
contributing factor could be the younger age that individuals with obesity enter LTCFs. Since
this research was limited in scope, statistics on confounding variables were not undertaken.
Other research looking at obesity in LTCFs, however, noted rates of dementia in persons residing
in a LTCF with obesity remained lower even after taking demographics such as age into account
(Ankuda et al., 2017; Cai et al., 2013). Dementia is notoriously difficult to diagnose (Parker et
al., 2020), and there is a high risk it has been underdiagnosed in the population newly residing in
LTCFs. The use of a dementia diagnosis, therefore, likely underestimates the extent of cognitive
impairments present in this population.
There is a complex relationship between dementia and obesity. On the one hand, obesity
increases the risk of developing dementia (Anjum et al., 2018; Ma et al., 2020), but having
obesity later in life has also been linked to a lower risk of dementia (Anjum et al., 2018; Dahl et
al., 2008). The pervasiveness of biases, including healthy survivor effect and pre-dementiadiagnoses weight loss, may account for some discrepancies (Anjum et al., 2018; Bowman et al.,
2019). There might be lower rates of dementia in the higher categories of the newly entered LTC
population because some treatments for dementia are associated with weight loss, and would

96
shift persons previously with obesity into lower BMI categories (Franx et al., 2017).
Interestingly, the ability for individuals with obesity to be able to lose weight during such
treatments contributes to the so-called ‘protective factor’ against mortality attributed to obesity in
older adults (de Souto Barreto et al., 2017; García-Ptacek et al., 2014). Either way, dementia is
prominent in the newly entered LTC population, and in-community management programs and
dementia specific alternatives to LTC will continue to be important in relieving the pressures
placed on LTCFs. While a Canadian national dementia strategy has been adapted, there are still
challenges in meeting growing demand for community-based dementia services (Estabrooks et
al., 2020; Morgan et al., 2015).
Obesity has increased in the general population, and with it there are concerns about the
concurrent rise in diabetes (Anis et al., 2010; Janssen, 2013; Ryan, 2009). Diabetes was present
in 26% of the persons newly residing in a LTCF. Unsurprisingly, persons newly residing in a
LTCF with obesity had higher rates of diabetes (39%) than their counterparts without obesity, a
finding generally reflected in studies in other countries (Ankuda et al., 2017; Cai et al., 2013;
Grabowski et al., 2005; Shieu et al., 2022). While diabetes was present in every BMI category,
rates were generally higher as BMI increased, peaking at rates of 48% for those with class III
obesity. Research into discrete obesity categories in LTCFs is more limited, but the literature
available shows that women over 70 demonstrated positive relationship with diabetes and
increasing BMI (Van Uffelen et al., 2010). A study by Zhang et al. (2019), for instance, reported
the odds of having diabetes in LTCFs were two-, three- and four-times higher for those with
class I, II or III obesity respectively as compared to their normal BMI counterparts.
Diabetes in LTCFs has been highlighted in the literature for its challenges. The
management of diabetes is impacted by LTC staff who have self-reported poor knowledge in

97
caring for diabetes in the LTC setting (Lega et al., 2020), with a disconnect between what
physicians' believe diabetes management should achieve and its actualization in LTCFs (Osman
et al., 2016). Recent research in Toronto, Canada, has also highlighted the potentially unsafe,
overly controlled treatment of diabetes amongst older adults in LTCFs (Lega et al., 2021). There
is already much effort in managing diabetes in-community, and the information here highlights
that diabetes is prominent in LTC settings, especially amongst the population with higher rates of
obesity.
Individual programs for chronic conditions, such as diabetes or dementia, are important
in keeping Canadians out of LTC, but the ability to access healthcare professionals confident in
their ability to help manage multiple conditions plays a role as well. The presence of multiple
morbidities (2+) was higher amongst those with obesity, and with increasing obesity. Those with
obesity, especially class II obesity had the highest rates of having 4 and especially 5+ conditions.
Previous literature has found that the number of conditions older adults had increased with age
over 50 (Machado et al., 2013), and also with increasing BMI (Amankwaa et al., 2022; Machado
et al., 2013). Older adults with multiple chronic conditions faced increased hospitalization and
readmission rates (Rodrigues et al., 2022), increased LTC admission, and increased mortality
(Halonen et al., 2019; Viljanen et al., 2021). The management of multiple chronic conditions in
community is important to delay entrance into LTC, especially for those with obesity. However,
healthcare workers felt underprepared when helping older Canadians living in-community
manage multiple chronic conditions (Ploeg et al., 2019). One of the goals of management of such
conditions is ensure that the condition(s) do not negatively impact the ability to function
independently or semi-independently in-community.

98
Having a chronic condition, such as dementia or diabetes, or else multiple conditions,
does not translate directly into impairment, however, the progression or mismanagement of such
conditions may lead to disability. Activities of daily living (ADLs) are benchmark activities that
give some indication of functional capabilities. Persons newly residing in a LTCF with obesity,
regardless of dementia status, had higher or equal rates of independence for each of the ADLs,
with little exception. However, persons newly residing in a LTCF with obesity were also more
likely to need two+ person assistance.
Interestingly, persons newly residing in a LTCF with class I obesity or an overweight
BMI had similar levels of independence in their ADLs, and both had higher independence levels
than their counterparts with normal BMI. This held true for the groups with and without
dementia. As there is debate about the threshold of the health risks associated with obesity for
older adults (Amankwaa et al., 2022; de Souto Barreto et al., 2017) these results provide some
evidence in favor of not being overly concerned about lower levels of obesity levels in older
adults in LTCFs, as independence levels indicated among those with overweight or class I
obesity could be seen as an indication for overall health. However, the results also show that
there is an upper limit to the association of greater independence seen with obesity in older
adults. Independence levels begin to taper off with class II obesity, with class III obesity
exhibiting lower levels or equal levels of independence compared to the normal weight group.
While overall independence levels were higher amongst those with obesity, the data also showed
that when assistance was needed it was more likely to be extensive.
Persons newly residing in a LTCF with obesity were more likely to need two+ person
assistance in performing ADLs, a finding also reflected in previous research (Harris et al., 2018;
Kosar et al., 2018). Such assistance translates to a higher usage of staffing resources. Barriers

99
form when funding algorithms do not allow appropriate compensations, as facilities become less
likely to accept obese patients due to an increase in the reduction of quality of care and an
increase in staff injuries (Ankuda et al., 2017; Bariatric Safe Patient Handling and Mobility
Guidebook Professional Advisory Group, 2015; Muir & Archer-Heese, 2009). American
researchers have criticized their funding models where increased obesity rates have not been met
with increased staffing hours per person (Harris et al., 2018). Canadian policies and funding
models should be examined to determine if funding strategies take into account higher rates of
two+ person assistance, and other bariatric specific care needs. In Ontario, for example, LTC
funding is provided as a per diem per bed type (e.g., long-term, short-term), which includes
assigned staffing hours (Ontario Ministry of Long-Term Care, 2022). The total funding from
these per diems are then adjusted based on based on Case Mix Index (CMI) and Resources
Utilized Groups (RUGs) scores, both of which rely upon the RAI-MDS 2.0 assessments (Ontario
Ministry of Long-Term Care, 2022). This assessments have been criticized by health
practitioners for not accurately reflecting the needs of persons residing in a LTCF with bariatric
care requirements, however there is little to no research linking this characteristic with
weaknesses in the assessment (Sutherland et al., 2013), additionally, both the CMI and RUGs do
not include two+ person assistance in their calculations (Canadian Institute for Health
Information, 2018). Recognizing the higher staffing needs per patient with higher obesity has
been suggested as a way of addressing some of the barriers faced by those with obesity
attempting to access LTC (Felix et al., 2018). It is unknown how such a funding model in a
Canadian context, with its mix of private, public-profit, and public-non-profit facilities, would
impact the willingness or ability for LTCFs to able to accept individuals with obesity.

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The Limitations and Usefulness of BMI Categories Amongst Persons Newly Residing In a
LTCF
The risk of requiring bariatric equipment increases with weight and does not rely upon
BMI. Bariatric equipment is generally required for those with a mass of 115 kg (~250lbs) or
higher to ensure safety and quality of care (Felix et al., 2011; Caz Hales et al., 2019; Muir &
Archer-Heese, 2009). Accounting for only 2% of the total population over the ten-year period
(n=5,930), the demand for bariatric equipment increased nearly 50% as incidence of individuals
with both 115-135 kg or135-155 kg increased. The need for bariatric equipment, and the lack of
that equipment in facilities, can act as a barrier in obtaining access to LTC. Barriers include not
only the procurement of more expensive equipment, but also the capacity to accommodate (e.g.,
room, doorway, and hallway sizes) and store the bulkier equipment (Felix et al., 2011; Hahler,
2002; C. Hales et al., 2020; D. Jones et al., 2020). While the most recent edition of the voluntarybased Canadian standards for LTC planning and design included updated requirements for
dimension and clearances to accommodation bariatric spaces, (Canadian Standards Association,
2018), the extent to which facilities have been retrofitted to accommodate is an area that needs
be explored further. As the data shows, there has been an increase in the number of people at risk
of requiring bariatric equipment entering LTC. Such an increase in demand may be associated
with an increase in costs as facilities purchase, house and retrofit for such equipment (Felix et al.,
2011; C. Hales et al., 2020; Miles et al., 2012).
This study utilized obese and non-obese categories, alongside the six BMI categories, as
well as a weight only incidence analysis. Two observations were made. First, the weight only
analysis showed a greater rate of increase in the number of individuals who entered with a
bariatric weight (115kg) as compared to the BMI analysis of class II obesity and class III obesity.

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BMI analysis should not be solely utilized when looking to understand the supply and demand
balance of bariatric equipment in LTCFs. Second, the use of non-obese and obese continuously
masked the differences seen in the more extreme BMIs. The differences noted for the
demographics, prevalence of health conditions and independence levels of ADLs increased with
increasing obesity, however the effects of having class I obesity were often very similar to
individuals with an overweight BMI and normal BMI. The observations suggest that
consideration of 'obese' as a single group masks more prominent differences within this category
and may limit the potential contributions of data simplified to reporting characteristics defined as
simply obese when informing responsive practice and policies.
The Impacts of the COVID-19 Pandemic
It is beyond the scope of this thesis to attempt to measure or fully consider the impact of
COVID-19 across the LTC sector. The data analyzed here, however, does show a notable
decrease in the number of first initial assessments in 2020, and lower obesity rates then were
previously trending. The decrease in the number of first initial assessments was not seen at equal
rates across the regions, with BC and Alberta seeing little impact. Additionally, none of the 130+
facilities from Saskatchewan, which otherwise would account for 60% of the 'Other' group, were
included in the CCRS dataset from CIHI for the fiscal year 2020/21. This discrepancy
contributed to the anomaly of 2020 data. The decreases noted elsewhere could be for a variety of
reasons, including a slowing of new admissions or entries and re-entries from acute care facilities
(Jeffords, 2021; Sibbald, 2020), Ontario for example temporarily stopped admitting people into
LTC in mid-April 2020 and only resumed in facilities without active outbreaks (Sibbald, 2020).
The lower numbers were reflected in a drop in healthcare access across the system, including alladmissions to LTC (Canadian Institute for Health Information, 2021b) and non-COVID-19

102
related hospital admissions (Canadian Institute for Health Information, 2021a). These alladmission to LTC remained low through the end of 2020 in contrast to the recovery in other
healthcare sectors (Canadian Institute for Health Information, 2021b; A. Jones et al., 2022). Due
to the nature of the data, it is unknown whether initial assessments for admission reflected this
delay in recovery.
Along with a drop in overall numbers of new LTC admissions, the rate of obesity was
notably lower in 2020. The non-homogenous decrease in initial assessment numbers across
regions may have impacted the overall obesity rates, since Ontario had some of the highest rates,
and BC the lowest. It is not known how COVID-19 impacted weight biases and barriers for
accessing healthcare services. Increased isolation impacted the entire population, however those
with reported higher risks of complications of COVID, which included older adults and those
with obesity, may have had different experiences. Policies encouraging the exit of persons
residing in a LTCF most capable of leaving LTC, may have disproportionately impacted persons
with obesity, as they were generally younger, with higher rates of independence. While other
research is emerging looking at LTC populations pre-pandemic, and during pandemic (A. Jones
et al., 2022), it may serve well for future research to include an obesity specific lens in their
research on COVID-19 in LTCFs.
A Priority Population
As Patychuk & Seskar-Hencic (2008) outline, ensuring healthcare equity first involves
the identification of priority populations, followed by an analysis of unique burdens and barriers,
and then identifying future steps in policy making. A priority population within the context of
healthcare has been described as "those that are experiencing and/or at increased risk of poor
health outcomes due to the burden of disease and/or factors for disease; the determinants of

103
health, including the social determinants of health; and/or the intersection between them"
(Ontario Ministry of Health and Long Term Care, 2018, p. 13). Individuals with obesity
experience increased health risks. First, the nature of obesity itself, or the burden of obesity,
results in an increased risk of poor health outcomes. Secondly, having obesity is directly related
to social determinants of health, as weight biases, obesity-specific barriers, and obesogenic
environments intersect to negatively impact health outcomes, including in LTC settings
(Bradway et al., 2017; Felix et al., 2016; Caz Hales et al., 2019; S. Kumanyika et al., 2002; Pearl
& Puhl, 2018; Phelan et al., 2015; Public Health Agency of Canada & Canadian Institute for
Health Information, 2011). Despite the complex challenges related to obesity, this population
remains underserved, with multiple sectors of the healthcare system possibly biased, unprepared,
and undereducated.
The LTC sector in Canada must not only adapt to serve an aging population but also one
that is characterized by increased rates of obesity. It is important to look more closely at whether
and how the population entering LTC is changing over time in order to adapt facilities and
processes to address explicit and implicit biases and barriers. Older adults in general, and persons
in LTCFs more particularly, are not homogenous groups. While the majority of persons newly
residing in a LTCF do not have obesity, there is an important and apparently growing segment of
the population with varying levels of obesity. These persons newly residing in a LTCF exhibit
particular patterns of health issues, independence levels, needs for assistance and social, and
psychological and emotional needs that require special recognition and attention to ensure health
equity.

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Chapter Six: Conclusion and Recommendations
This thesis is intended to begin filling gaps in our understanding of obesity in Canadian
long-term care (LTC). Obesity in other countries is associated more generally with an increased
risk for admission to LTC, risk of entrance at younger ages, and higher costs of care in LTCFs.
Having obesity is also known to act as a barrier to obtaining entrance to LTCFs and, once in
LTCFs, obesity is known to act as a barrier to receiving high quality of care. The research
presented here offers unique insights into the population first entering LTC and thus undergoing
an important point of transition. The CCRS dataset from CIHI collected through initial
assessments provides the opportunity to retroactively look at this transitioning population over a
ten-year period and utilize previously untapped weight and height measurements to understand
better the presence and implications of obesity in this population. The focus of this research
therefore provides opportunities to consider not just the needs and concerns of those entering
LTC with obesity, but also ways to consider preventative and management interventions aimed
at delaying entry to LTC.
Limitations
Geography
While the CIHI CCRS dataset analyzed in this thesis was large, caution should be
exercised when seeking to generalize the findings to the Canadian population of persons newly
residing in a LTCF. The provinces of Quebec, Prince Edward Island, New Brunswick, most of
Nova Scotia, along with the Northwest Territories and Nunavut were not included in the dataset.
Based on the number of persons residing in LTCFs CIHI CCRS reported for in fiscal year
2016/17, roughly 75% of all persons residing in Canadian LTCFs are included in the full CCRS
data set (Canadian Institute for Health Information, 2017c; Statistics Canada, 2017a).

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The rural and urban designation of a resident's last location was limited by the simplified
definition of urban and rural, wherein urban was defined as a population of more than 10,000
people (Canadian Institute for Health Information, 2022a). Rural and smaller urban centres are
not homogenous in their challenges (Gatrell & Elliott, 2009). Major differences in healthcare
provisions and utilization created by geographical settings extend well beyond a minimum
population threshold between ‘urban’ and ‘rural’. The geographical and social distinguishing
features of communities based on size and distance would be expected to impact LTC,
alternatives to LTC, in-community programs and individual capacities. For these reasons, the
data analyzed here are incapable of capturing nuance in the strengths and resilience of rural
communities and facilities.
Assessments
The nature of the initial assessment data was limited in its capturing of chronic
condition's severity or influence on entrance, some demographic information, facility
characteristics, and BMI category thresholds. Initial assessments provided rates of chronic
conditions; however, there is no context for individual severity or progression of illness. The
presence of a chronic condition may not be directly related to the cause of the need for LTC.
This lack of contextual information is a limitation of the study, and the literature would benefit if
the major contributing factors for LTC were better highlighted.
The demographic information made available to this thesis was limited by the assessment
itself, but even some of the demographic information collected in the assessment has been
suppressed by CIHI for reasons of confidentiality. Further research would do well to collect and
examine more demographic information, including socio-economic considerations (e.g.,
household income, level of education attained), expanded gender identities, sexual orientations,

106
ethnic identity, and immigration status, to further enrich the demographic profile of persons with
obesity in and entering LTC. Some of these demographic features have been found to be
confounders for contributing to the risks of gaining weight (e.g., socio-economic), and for
affecting obesity related health risks (e.g., lower thresholds of risks for certain ethnicities
(Rueda-Clausen et al., 2020). Other demographics may have an interactive effect with obesity
when looking to access LTC since, separately, obesity and, for example, immigrations status
(Castañeda et al., 2015; Qureshi et al., 2021) or LGBTQ+ status are each associated with a
greater risk of encountering barriers to entering LTC.
Facility characteristics are prominent influences for obesity-based barriers (Bradway et
al., 2017; Felix et al., 2016; Harris et al., 2020; Zhang et al., 2013). While the data allowed for an
individual’s last location prior to entry into LTC, this did not mean the LTCF had the same rural
or urban designation. Rural and small community LTCFs may have organizational, structural,
and financial hurdles that are exacerbated by their geographical settings. Geography is one of
many characteristics that would influence the capacity and willingness of facilities to accept
individuals with larger levels of obesity in a Canadian context. Other contextual characteristics
might include private or public ownership, case mix, or multi-facility affiliation (Zhang et al.,
2013). It is a limitation that obesity rates could not be compared based upon facility
characteristics and this is a point for future research to consider.
The Body Mass Index (BMI) was utilized as height and weight were collected in the
initial assessments of the persons newly residing in LTCFs. BMI, in general, provides a simple
measurement that quickly, but crudely, captures increased health risks associated with increasing
adipose tissue while taking height into account. As mentioned previously, the use of BMI brings
concern for its validity as a health metric (e.g., at the individual level, BMI does not distinguish

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tissue type or accumulation location). However, BMI can be useful for population level studies.
At a population level, BMI provides an estimate for increased health risks associated with
increasing obesity, where the more inherent differences seen at an individual level are balanced
out and general trends can be observed. The use of BMI at a population level, nevertheless, has
noteworthy limitations. The standard WHO BMI health risk thresholds are based predominately
on younger-adult and Eurocentric populations (Barba et al., 2004; S. K. Kumanyika, 2019;
Razak et al., 2007; Rueda-Clausen et al., 2020). The sample population in this study is comprised
largely of older-adults and includes persons of non-European origin. Future research would do
well to consider BMI thresholds that are age- and ethnicity-adjusted.
Finally, the data is imitated to only three WHO obese sub-categories (classes I-III). The
Canadian Guidelines lay out five sub-categories of obesity; however, due to the small number of
individuals in these higher groups (approximately 10,000 individuals entered with class III
obesity over the ten years), CIHI only provided three sub-categories. The nuanced differences in
heavier populations are lost, and the number of individuals at these weights in Canadian LTC is
still unknown.
Missing Data
Data with larger portions of missing data and/or low confidence were eliminated (i.e.,
RUGs, neighbourhood income, and education). Resources Utilized Groups (RUGs) scores and
education were missing from 40% and 30% of persons newly residing in a LTCF respectively.
Neighbourhood income was provided by quintile, but the distribution was affected by the
removal of over 20% of the assessments during the data clean-up phase. Both education and
neighbourhood income were analyzed in cross-tabulations with BMI, but produced no notable

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differences and, due to low confidence from the number of missing values, they were not
included in the results.
Selection Bias
The assessment data collected for this study reflects those individuals that have
successfully gained entrance into a LTCF. As discussed, the literature has found that those with
obesity face barriers when accessing LTC, such as equipment availability (Miles et al., 2012)
and attitudes of staff (Felix et al., 2011). It is not known to what extent persons with obesity
face barriers when trying to access Canadian LTC, and the sample population reflects the bias
of only providing information on those able to contend successfully with such challenges. The
sample population may be, biased towards those persons with obesity that are seen as most
profitable, such as short-term stays, as was highlighted in the literature (Harris et al., 2020;
Zhang, Lu, et al., 2019). The selection bias also impacts the observations of obesity incidence
rates. While the LTC sector has newer Canadian Standards for increased accessibility, including
considerations for the bariatric facilities, the extent to which these voluntary guidelines have
been pursued is unknown. The incidence rates reported in this study reflect the capacity for the
LTC sector to be able to accept bariatric and other persons with higher levels of obesity. It is
unknown how many bariatric beds are available in LTCFs, what their occupancy rates are, and
what unmet need exists. Having adequate numbers of suitable beds in an accessible manner (for
example within a geographically reasonable distance from home) would reduce barriers.
However, operating with a surplus of bariatric beds, resulting in low occupancy rates of those
beds, may increase the barriers faced by persons without obesity as costs as this equipment
cannot be safely utilized by persons of a non-bariatric stature. Further explorations of unmet

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needs for LTC among the population with obesity are needed to better understand the real
demand for LTC from this group.
The Population Newly Admitted to LTC with Obesity
The Canadian literature lacks research on the population with obesity in LTCFs. As one
step towards addressing this gap in knowledge, this thesis looks at obesity amongst those newly
admitted to LTC. Nearly 20% of the population entering LTC had obesity, and 7% had class II or
III obesity. The rate of obesity in this group remained relatively constant, with moderate growth
between 2010 and 2020 and a greater increase in the proportion of persons with the heaviest
BMIs (class II and class III obesity). It is difficult to say if this is in line with other research on
obesity rates in LTCFs as this study is limited to those newly admitted and not the entire
population. Previous research looking at obesity rates in LTCFs reported an increase between
1992-2002 (Lapane & Resnik, 2006), 1999-2013 (Marihart et al., 2015) and 2005-2015 (Zhang,
Field, et al., 2019), but these studies were conducted somewhat earlier than the research reported
in this thesis. There is some indication, for instance, that rates of increase in adult population
obesity began leveling off after 1999 (Rokholm et al., 2010). Like previous research, the profile
of persons newly residing in a LTCF with obesity describes a heterogeneous population more
likely to be female and younger, with higher rates of diabetes and multi-morbidities but lower
instances of dementia. The population also had higher independence rates generally yet was
more likely to require two+ person assistance. The data demonstrated that persons newly residing
in a LTCF with lower levels of obesity (class I) were similar to overweight and normal BMI
counterparts with respect to levels of conditions and care needs, adding to the debate of BMI
health risks thresholds for older adults with obesity.

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The data here adds to the literature that persons with obesity and higher levels of obesity
are more likely to be transitioning into Canadian LTC at younger ages and more likely to have
diabetes at the time of transition and emphasizes the heterogeneity of the LTC population. Two
main sub-populations are identified, younger-older adults with obesity and older adults with
obesity, (with a spectrum between them) with different considerations for care within LTCFs and
preventative services. These populations are united in their obesity in that the management of
obesity is complex in LTCFs; there are higher rates of obesity-related conditions such as
diabetes, the social and health implications of facing weight biases in the healthcare system, and
obesity-based barriers when trying to access LTC or other alternatives. However, the populations
also differ in the management of obesity. Older adults should focus on maintaining weight rather
than losing weight, as may be prescribed to younger people. Finally, there are different social,
emotional, and physical needs for younger-older adults than what is provided in LTC settings
tailored to an older population.
Implications
The demand for LTC is projected to double by 2040, so encouraging the education,
management and treatment of obesity, diabetes and dementia in the community may alleviate
some of that pressure. Preparing for the future of an aging population goes beyond creating new
facilities and beds and requires creating space for facilities to anticipate and accommodate
changing needs in LTCFs, such as those that come with rising rates of obesity and bariatric care.
New LTCFs should be designed to house bariatric equipment and efforts are needed to retrofit
existing facilities to handle such equipment. A key implication of this study is the evidence it
presents that the number of individuals with higher levels of obesity (class II and class III) and
those at risk of needing bariatric equipment has grown. Efforts are needed to evaluate and most

111
likely increase care services and infrastructure of LTCFs to be able to support persons residing in
a LTCF across the full BMI spectrum. Concurrently strengthening obesity, diabetes and
dementia home support and management programs (including education of health practitioners)
may help to delay or prevent LTC and encourage transitioning out of LTC. Additionally, more
expensive acute care settings (i.e., hospitals) may also benefit from such investments as those
waiting in acute settings are able to transition into LTC, or into community with proper supports.
Research into the adequacy of LTC meeting the population demands needs to include
obesity as a factor for needing LTC and as a barrier to accessing that LTC. It is unknown what
the current unmet demands for the care of individuals with higher levels of obesity are and how
these demands differ across the healthcare geographies. Likewise, it is unknown what the levels
of supply, accessibility levels, and occupancy rates are for bariatric and obesity focused care and
equipment.
Knowledge Dissemination
There are three identified audiences for this thesis – academic researchers, policy makers
and administrators, and healthcare providers and practitioners. For the academic audience,
preliminary findings were presented at two conferences, the Canadian Association of
Geographers in May 2022, and the Western Division of the Canadian Association of
Geographers in March 2023. I intend to prepare a manuscript for peer review with the goal of
publishing in an academic journal (e.g., Obesity, Journal of Gerontology, Journal of Nutrition,
Health, and Aging). The thesis will be made publicly available via Library and Archives Canada.
Recommendations for Future Actions and Research
To increase the understanding of the population newly entered into LTC with obesity,
future research should look more closely at broader demographic factors such as gender,

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sexuality, ethnicity, and immigration status. Additionally, the care needs and independence of the
population with a bariatric weight and higher levels of obesity (class II and class III) should be
further examined. While this thesis captured the population newly entered into LTC, future
research should expand to analyse the of levels of obesity and their relation to care needs of
those living in LTCFs, including mortality and morbidity rates, length of stays, and resource
utilization. There are many areas, including healthcare provider education, in-community chronic
conditions programs, and in-LTC chronic condition management policies that would benefit
from including a lens of obesity in research and policy.
This thesis provided background quantitative data. There is a need, however, for
qualitative research to understand better the experiences of persons in LTCFs (newly entered and
already living in LTCFs), and older adults with obesity living in community settings but showing
signs of needing LTC. Such research should also include the experiences of family and support
systems of these individuals. It is also important to learn more about the experiences and
perceptions of LTC administrators and healthcare providers, such as what shortfalls in LTCFs
exist for persons residing in a LTCF with obesity regarding care, policy, and administration.
Qualitative research and internal audits should also look at two areas of concern raised in the
literature. The first is the potential presence of obesity-based barriers when accessing LTC, and
the second, which contributes to the first, is the ability for LTC to meet current and future
demands for bariatric and higher obesity care.

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Hypertension
Dementia other than Alzheimer’s disease
Arthritis
Diabetes mellitus
Osteoporosis
Depression
Allergies
Cerebrovascular accident (stroke)
Gastrointestinal disease
Hypothyroidism
Other cardiovascular disease
Emphysema/ COPD
Congestive heart failure
Alzheimer’s disease
Anemia
Arteriosclerotic heart disease (ASHD)
Renal failure
Cancer
Cataracts
Anxiety disorder

Health Condition

(N=350,348), 2010-2020

Total Population
(100%, N=350348)
%
n
(212,511)
61
(155,217)
44
(123,708)
35
(91,809)
26
(76,020)
22
(75,829)
22
(69,289)
20
(65,116)
19
(61,680)
18
(59,677)
17
(58,273)
17
(56,617_
16
(51,277)
15
(43,702)
12
(39,964)
11
(39,127)
11
(38,091)
11
(37,877)
11
(34,059)
10
(31,519)
9

Body Mass Index (kg/m2)
<30
≥30
81%, n= 283840
19%, n= 66508
%
n
%
n
59
(168,520)
66
(43,991)
46
(131,406)
36
(23,811)
34
(95,848)
42
(27,860)
23
(65,673)
39
(26,136)
23
(65,386)
16
(10,634)
21
(58,958)
25
(16,871)
19
(53,709)
23
(15,580)
19
(53,099)
18
(12,017)
17
(49,370)
19
(12,310)
17
(47,257)
19
(12,420)
16
(46,334)
18
(11,939)
16
(44,344)
18
(12,273)
13
(38,216)
20
(13,061)
13
(37,174)
10
(6,528)
12
(33,047)
10
(6,917)
11
(30,941)
12
(8,186)
10
(29,353)
13
(8,738)
11
(31,544)
10
(6,333)
10
(27,839)
9
(6,220)
9
(25,099)
10
(6,420)

Frequency of Health Condition in the Population of Persons Newly Residing in a Long-term Care Facility and by Obesity Status

Appendix 1

Appendices

139

Urinary tract infection in last 30 days *
Glaucoma
Cardiac dysrhythmia
Macular degeneration
Hip fracture
Parkinson’s disease
Peripheral vascular disease
Transient ischemic attack (TIA)
Antibiotic resistant infection (e.g., Methicillin resistant staph)
Asthma
Hemiplegia/hemiparesis
Seizure disorder
Aphasia
Pneumonia
Hypotension
Schizophrenia
Pathological bone fracture
Bipolar disorder (Manic depressive)
Liver disease
Wound infection
Deep vein thrombosis
Traumatic brain injury *
Hyperthyroidism *
Missing limb (e.g., Amputation)
Multiple sclerosis
Cellulitis
Respiratory infection
Clostridium difficile
Diabetic retinopathy
Viral hepatitis *
Cerebral palsy
Paraplegia
8
7
7
7
6
6
6
4
4
4
4
4
3
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
<1
<1
<1
<1

(26,894)
(25,438)
(25,030)
(23,685)
(22,334)
(21,504
(19,326
(15,100
(15,008
(13,596
(13,407
(12,694
(12,262
(6,926
(6,163
(6,248
(5,168
(5,313
(4,854
(4,972
(3,730
(3,762
(3,450
(3,340
(3,347
(3,583
(2,937
(2,330
(1,704
(1,645
(1,080
(1,045)

8
8
7
7
7
6
5
4
4
3
4
4
4
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
<1
<1
<1
<1

(21,802)
(21,439)
(20,078)
(19,996)
(19,790)
(18,412)
(14,655)
(12,472)
(11,754)
(9,683)
(10,637)
(9,954)
(10,465)
(5,741)
(4,304)
(5,374)
(3,643)
(4,163)
(3,724)
(3,680)
(3,077)
(2,712)
(2,274)
(2,743)
(2,531)
(2,443)
(2,338)
(1,976)
(1,097)
(1,317)
(799)
(740)

8
6
7
6
4
5
7
4
5
6
4
4
3
2
3
1
3
2
2
2
1
2
2
1
1
1
1
1
1
<1
<1
<1

(5,092)
(3,999)
(4,952)
(3,689)
(2,544)
(3,092)
(4,671)
(2,628)
(3,254)
(3,913)
(2,770)
(2,740)
(1,797)
(1,185)
(1,944)
(789)
(1,670)
(1,005)
(1,248)
(1,174)
(685)
(1,018)
(1,309)
(707)
(816)
(897)
(599)
(354)
(607)
(328)
(281)
(305)

140

<1
<1
<1
<1
<1
<1
<1
<1

(841)
(814)
(682
(659)
(616)
(305)
(236)
(213)

<1
<1
<1
<1
<1
<1
<1
<1

(688)
(617)
(523)
(589)
(500)
(258)
(186)
(196)

<1
<1
<1
<1
<1
<1
<1
<1

(153)
(197)
(159)
(70)
(116)
(47)
(50)
(17)

Note. * Indicates the conditions which are not significantly different (p>0.001). All other conditions are significantly different between
the obese (≥30 kg/m2) and non-obese (<30 kg/m2) groups (p≤0.001).

Amyotrophic lateral sclerosis (ALS) *
Septicemia
Quadriplegia *
Huntington’s chorea
Conjunctivitis *
HIV infection *
Sexually transmitted diseases *
Tuberculosis (active)

141

Hypertension
Dementia other than
Alzheimer’s disease
Arthritis
Diabetes mellitus
Osteoporosis
Depression
Allergies
Cerebrovascular accident
(stroke)
Gastrointestinal disease
Hypothyroidism
Other cardiovascular disease
Emphysema/ COPD
Congestive heart failure
Alzheimer’s disease
Anemia
Arteriosclerotic heart
disease (ASHD)
Renal failure
Cancer
Cataracts
Anxiety disorder

Health Condition

(N=350,348), 2010-2020

(n)
(20,757)
(17,662)
11,799)
(5,740)
(12,153)
(7,754)
(7,245)
(6,236)
(6,794)
(6,390)
(5,651)
(8,356)
(4,721)
(4,185)
(5,243)
(3,544)
(3,357)
(4,537)
(3,791)
(3,714)

%
54*
46*
31*
15*
31*
20
19
16*
18
17
15*
22*
12
11*
14*
9*
9*
12
10
10*

10
11
10
9

17
17
16
15
13
13
12
11

33
22
24
20
18
19

%
59
47

(15,050)
(16,221)
(14,319)
(12,780)

(25,102)
(24,227)
(23,695)
(21,960)
(18,921)
(19,671)
(17,279)
(15,642)

(48,172)
(31,586)
(34,640)
(29,657)
(26,953)
(27,402)

(n)
(85,858)
(69,275)

Normal
(42%, n=14,6224)

Underweight
(11%, n= 38,671)

11*
11
10
9

18
17
17*
14*
15*
13
11*
12*

36*
29*
19*
22*
20*
20*

%
63*
45*

(10,946)
(10,786)
(9,729)
(8,605)

(17,474)
(16,640)
(16,988)
(14,028)
(14,574)
(13,318)
(10,525)
(11,755)

(35,877)
(28,347)
(18,593)
(21,547)
(19,511)
(19,461)

(n)
(61,905)
(44,469)

(28%, n=98,945)

12*
10*
10
9

18*
18*
18*
17*
18*
11*
10*
12*

41*
36*
17*
24*
22*
19

%
66*
40*

(5,127)
(4,046)
(3,986)
(3,763)

(7,570)
(7,386)
(7,464)
(6,913)
(7,441)
(4,720)
(4,253)
(5,102)

(16,790)
(14,732)
(6,935)
(9,903)
(9,012)
(7,871)

(n)
(27,072)
(16,580)

(12%, n=41,279)

Body Mass Index (kg/m2)
Overweight
Class I

14*
9*
9
10*

19*
20*
18*
20*
22*
8*
11
13*

44*
44*
15*
27*
25*
18

%
68*
33*

(2,081)
(1,403)
(1,346)
(1,526)

(2,833)
(2,913)
(2,656)
(2,967)
(3,183)
(1,253)
(1,589)
(1,878)

(6,489)
(6,442)
(2,250)
(3,939)
(3,675)
(2,610)

(n)
(10,010)
(4,824)

(4%, n=14,789)

Class II

15*
8*
9
11*

18
20*
17
23*
23*
5
10*
12

44*
48*
14*
29*
28*
15*

%
66*
23*

(1,530)
(884)
(888)
(1,131)

(1,907)
(2,121)
(1,819)
(2,393)
(2,437)
(555)
(1,075)
(1,206)

(4,581)
(4,962)
(1,449)
(3,029)
(2,893)
(1,536)

(n)
(6,909)
(2,407)

(3%, n=10440)

Class III

Health Condition Rates in the Population of Persons Newly Residing in a Long-term Care Facility by Body Mass Index (BMI) Status

Appendix 2

142

Urinary tract infection in last
30 days
Glaucoma
Cardiac dysrhythmia
Macular degeneration
Hip fracture
Parkinson’s disease
Peripheral vascular disease
Transient ischemic attack
(TIA)
Antibiotic resistant infection
(e.g., Methicillin resistant
staph)
Asthma
Hemiplegia/hemiparesis
Seizure disorder
Aphasia
Pneumonia
Schizophrenia
Hypotension
Bipolar disorder (Manic
depressive)
Pathological bone fracture
Wound infection
Liver disease
Traumatic brain injury
Deep vein thrombosis
Cellulitis
Hyperthyroidism *no sig.
differences
Multiple sclerosis
Missing limb (e.g.
Amputation)
Respiratory infection

(3,106)
(3,118)
(2,475)
(2,945)
(3,997)
(2,528)
(2,024)
(1,480)
(1,724)
(1,275)
(1,139)
(1,232)
(1,357)
(1,070)
(460)
(812)
(374)
(675)
(599)
(435)
(335)
(297)
(229)
(402)
(405)
(369)
(415)

8
8
6*
8
10*
7
5
4*
4
3
3*
3
4
3*
1
2
1
2
2
1
1*
1
1
1
1*
1
1*

1

1
1

2
1
1
1
1
1
1

3
4
3
4
2
1
2
1

4

8
7
7
7
7
5
4

8

(1,178)

(1,208)
(1,178)

(2,240)
(1,886)
(1,863)
(1,644)
(1,307)
(1,080)
(1,373)

(4,759)
(5,418)
(5,101)
(5,445)
(2,951)
(2,031)
(2,921)
(1,691)

(5,974)

(11,228)
(10,310)
(10,514)
(10,588)
(9,820)
(7,367)
(6,439)

(11,257)

1

1
1

1*
1
1
1
1*
1
1

4*
4*
4
4
2*
2*
2*
2

4

7*
7
7*
5*
6*
5
5

8

(745)

(918)
(896)

(1,248)
(1,239)
(1,382)
(1,098)
(1,108)
(965)
(968)

(3,649)
(4,080)
(3,621)
(3,663)
(1,720)
(1,813)
(1,641)
(1,578)

(4,056)

(7,093)
(7,293)
(6,537)
(5,205)
(6,064)
(5,264)
(4,553)

(7,439)

1

1*
1*

1
1
2*
1
1*
1
1

5*
4*
4
3*
2
3*
1*
2

4

6*
7
6*
4*
5*
6*
4

7

(382)

(458)
(441)

(571)
(618)
(655)
(445)
(596)
(585)
(415)

(2,071)
(1,783)
(1,601)
(1,244)
(726)
(1,053)
(546)
(903)

(1,808)

(2,554)
(3,037)
(2,500)
(1,691)
(2,204)
(2,598)
(1,767)

(3,082)

1

1*
1*

2
2*
2*
1
2*
2
1

6*
4*
5*
3*
2
4*
1*
3

5*

6*
7
5*
4*
4*
7*
4*

8

(110)

(195)
(220)

(236)
(327)
(309)
(153)
(239)
(332)
(166)

(928)
(630)
(672)
(373)
(259)
(520)
(150)
(417)

(775)

(880)
(1,076)
(760)
(550)
(599)
(1,098)
(544)

(1,172)

1

2*
2*

2
3*
2*
1
2*
4
1

9*
3
4*
*2
2
4*
1*
3

*6

5*
8
4*
3*
3*
9*
3*

8

(107)

(163)
(236)

(198)
(303)
(210)
(87)
(183)
(392)
(126)

(914)
(357)
(467)
(180)
(200)
(371)
(93)
(350)

(671)

(565)
(839)
(429)
(303)
(289)
(975)
(317)

(838)

143

(383)
(77)
(191)
(172)
(87)
(102)
(85)
(71)
(126)
(72)
(52)
(24)
(52)

1*
<1*
<1
<1*
<1
<1
<1
<1
<1
<1
<1
<1
<1*

<1

<1
<1
<1
<1
<1
<1

1
<1
<1
<1
<1
<1

(99)

(308)
(268)
(344)
(265)
(147)
(96)

(1,062)
(532)
(700)
(362)
(381)
(392)

<1

<1
<1
<1*
<1
<1
<1

1*
<1*
<1
<1
<1
<1

(45)

(224)
(184)
(119)
(163)
(59)
(66)

(531)
(488)
(426)
(265)
(272)
(194)

<1

<1
<1
<1*
<1
<1
<1

1*
1*
<1
<1
<1*
<1

(12)

(113)
(92)
(54)
(71)
(31)
(29)

(214)
(296)
(202)
(147)
(161)
(95)

Note. * Significant difference from the reference group (normal BMI (18.5-24.9 kg/m2)) (p≤0.001).

Clostridium difficile
Diabetic retinopathy
Viral hepatitis
Cerebral palsy
Paraplegia
Amyotrophic lateral
sclerosis (ALS)
Septicemia
Quadriplegia
Huntington’s chorea
Conjunctivitis
HIV infection
Sexually transmitted
diseases
Tuberculosis (active)
<1

<1
<1
<1
<1
<1
<1

1
1*
<1
<1*
1*
<1

(4)

(50)
(34)
(13)
(29)
(7)
(12)

(77)
(180)
(68)
(67)
(79)
(37)

<1

<1
<1
<1*
<1
<1
<1

1
1*
1
1*
1*
<1

(1)

(34)
(33)
(3)
(16)
(9)
(9)

(63)
(131)
(58)
(67)
(65)
(21)

144

16 (57,308)
34 (118,820)
9 (31,201)

Extensive Assistance

Total Dependence

12 (40,830)
18 (63,132)
32 (111,117)
15 (53,621)
1 (2,186)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur
27 (95,749)
15 (52,811)
12 (43,375)
8 (29,728)

Independent

Supervision

Limited Assistance

Extensive Assistance

Walking in Room

23 (79,462)

Independent

Transfer

<1 (178)

9 (32,377)

Limited Assistance

Did not Occur

32 (110,464)

Supervision

Total
(100%, N=350,348)
% (n)

Independent

Bed Mobility

Activity Daily Living
Self Performance

(N=350,348), 2010-2020

9^ (24,584)

13^ (35,618)

15^ (43,066)

27^ (77,895)

1 (1,823)

15 (42,453)

32 (89,963)

18 (51,582)

12 (33,196)

23^ (64,823)

<1 (127)

9 (25,238)

33 (94,969)

16^ (46,742)

9^ (26,544)

32^ (90,220)

<30 kg/m2
(81%, n=283,840)
% (n)

<or ≥ 30 kg/m2

8 (5,144)

12 (7,757)

15 (9,745)

27 (17,854)

1 (363)

17 (11,168)

32 (21,154)

17 (11,550)

11 (7,634)

22 (14,639)

<1 (51)

9 (5,963)

36^ (23,851)

16 (10,566)

9 (5,833)

30 (20,244)

≥ 30 kg/m2
(19%, n=66,508)
% (n)

Activities of Daily Living (ADL) Self Performance of Persons Newly Residing in a Long-term Care Facility by Obesity Status

Appendix 3

145

36 (126,541)

Did not Occur

17 (59,881)
12 (41,444)
8 (27,328)
1 (2,133)
40 (139,346)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

19 (65,940)
14 (49,297)
18 (63,123)
19 (64,987)
3 (12,141)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

16 (57,709)
12 (42,613)
14 (49,172)
18 (64,091)
22 (78,571)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur
8 (27,582)
7 (25,128)
22 (77,539)
47 (165,877)

Independent

Supervision

Limited Assistance

Extensive Assistance

Dressing

17 (58,192)

Independent

Locomotion off unit

27 (94,860)

Independent

Locomotion on unit

23 (80,216)

Independent

Walk in Corridor

1 (2,144)

Total Dependence

47 (133,497)

22 (62,650)

7 (20,618)

8 (22,038)

23^ (65,039)

19^ (52,781)

14 (39,598)

12^ (34,687)

16 (46,782)

16 (44,953)

4^ (9,982)

19^ (53,935)

18 (51,106)

14^ (40,139)

19 (53,542)

26 (75,136)

39 (110,864)

1^ (1,813)

8^ (22,627)

12^ (34,280)

17^ (48,945)

23^ (65,311)

36 (100,838)

1^ (1,839)

49^ (32,380)

22 (14,889)

7 (4,510)

8 (5,544)

20 (13,532)

17 (11,310)

14^ (9,574)

12 (7,926)

16 (10,927)

20^ (13,239)

3 (2,159)

17 (11,052)

18 (12,017)

14 (9,158)

19^ (12,398)

30^ (19,724)

43 (28,482)

<1 (320)

7 (4,701)

11 (7,164)

16 (10,936)

22 (14,905)

39^ (25,703)

<1 (305)

146

<1 (287)

Did not Occur

10 (34,707)
8 (27,998)
6 (20,050)

Limited Assistance

Extensive Assistance

Total Dependence

8 (27,476)
18 (63,831)
42 (146,084)
18 (63,865)
<1 (754)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

8 (28,031)
21 (75,303)
45 (159,115)
17 (61,036)
<1 (137)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur
1 (3,769)
3 (11,714)
6 (20,941)
48 (169,726)

Independent

Supervision

Limited Assistance

Extensive Assistance

Bathing

8 (26,726)

Independent

Personal Hygiene

14 (48,338)

Independent

Toilet

<1 (196)

42 (147,032)

Supervision

Did not Occur

34 (120,365)

Independent

Eating

15 (53,935)

Total Dependence

48 (135,949)

6 (16,781)

3 (9,445)

1 (2,957)

<1 (109)

18^ (50,923)

45 (128,058)

21 (60,962)

8 (22,792)

7 (20,996)

<1^ (651)

18^ (52,025)

42 (117,806)

18 (51,864)

8^ (22,504)

14 (38,990)

<1^ (181)

6^ (17,831)

9^ (24,648)

10^ (29,252)

42 (118,105)

33 (93,823)

<1 (245)

16^ (44,792)

51^ (33,777)

6 (4,160)

3 (2,269)

1 (812)

<1 (28)

15 (10,113)

47^ (31,057)

22 (14,341)

8 (5,239)

9^ (5,730)

<1 (103)

18 (11,840)

43^ (28,278)

18 (11,967)

7 (4,972)

14^ (9,348)

<1 (15)

3 (2,219)

5 (3,350)

8 (5,455)

43^ (28,927)

40^ (26,542)

<1 (42)

14 (9,143)

147

37 (129,470)
4 (14,728)

Note: ^ Significantly larger when comparing obese and non-obese groups (p<0.05)

Total Dependence
Did not Occur

38^ (106,651)
4 (12,057)

34 (22,819)
4 (2,671)

148

8* (3,099)
17 (6,564)
37* (14,463)
12* (4,486)
<1 (27)

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

10* (3,724)
19 (7,170)
35* (13,724)
18* (7,080)
1* (503)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur
20* (7,885)
13* (4,885)
13 (5,093)
10* (3,698)

Independent

Supervision

Limited Assistance

Extensive Assistance

Walking in Room

17* (6,470)

Independent

Transfer

26* (10,032)

Supervision

9 (12,958)

13 (18,504)

15 (22,163)

28 (40,238)

1 (837)

15 (21,633)

32 (46,493)

18 (26,710)

12 (17,023)

23 (33,528)

<1 (55)

9 (12,967)

33 (48,745)

16 (24,063)

9 (13,683)

32 (46,711)

Underweight
Normal
(11%, n=38,671) (42%, n=146,224)
% (n)
% (n)

Independent

Bed Mobility

Activity of Daily Living
Self-performance

(N=350,348), 2010-2020

8* (7,928)

12* (12,021)

16* (16,018)

30* (29,772)

<1 (483)

14* (13,740)

30* (29,746)

18 (17,702)

13* (12,449)

25* (24,825)

<1 (45)

8* (7,785)

32 (31,761)

16 (16,115)

10* (9,762)

34* (33,477)

Overweight
(28%, n=98,945)
% (n)

8* (3,249)

12* (4,964)

15 (6,332)

29* (11,774)

<1 (190)

15 (6,285)

31 (12,895)

18 (7,249)

12 (4,997)

23 (9,663)

<1 (19)

8* (3,419)

34* (14,200)

16 (6,661)

9 (3,810)

32 (13,170)

8* (1,158)

11* (1,671)

14 (2,138)

26* (3,777)

1 (80)

17* (2,579)

33* (4,843)

17 (2,588)

11 (1,609)

21* (3,090)

<1 (11)

10 (1,409)

37* (5,468)

16 (2,330)

8* (1,249)

29* (4,322)

Class I
Class II
(12%, n=41,279) (4%, n=14,789)
% (n)
% (n)

Body Mass Index (BMI) Category

(21)

7* (737)

11* (1,122)

12* (1,275)

22* (2,303)

1* (93)

22* (2,304)

33 (3,416)

16* (1,713)

10* (1,028)

18* (1,886)

<1

11* (1,135)

40* (4,183)

15* (1,575)

7* (774)

26* (2,752)

Class III
(3%, n=10,440)
% (n)

Activities of Daily Living (ADL) Self Performance of Persons Newly Residing in a Long-term Care Facility by Body Mass Index

Appendix 4

149

12 (4,715)
9 (3,313)
1 (304)

Limited Assistance

Extensive Assistance

Total Dependence

15* (5,727)
14 (5,436)
20* (7,837)
26* (9,984)
5* (2,048)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

12* (4,694)
11* (4,332)
15* (5,808)
24* (9,145)
26* (10,158)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur
6* (2,252)
6* (2,219)
19* (7,516)
49* (18,909)

Independent

Supervision

Limited Assistance

Extensive Assistance

Dressing

12* (4,534)

Independent

Locomotion off unit

20* (7,639)

Independent

Locomotion on unit

48* (18,550)

14* (5,270)

Supervision

Did not Occur

17* (6,519)

43* (16,762)

1 (348)

Independent

Walk in Corridor

Did not Occur

Total Dependence

47 (68,450)

22 (32,428)

7 (10,618)

8 (11,249)

23 (33,704)

19 (27,269)

14 (20,485)

12 (17,975)

16 (24,104)

16 (22,687)

3 (4,984)

19 (27,931)

18 (26,461)

14 (20,825)

19 (27,620)

26 (38,403)

39 (56,416)

1 (954)

8 (11,983)

12 (17,899)

17 (25,317)

23 (33,655)

35 (51,397)

1 (964)

47 (46,138)

23* (22,706)

8* (7,781)

9* (8,537)

21* (21,177)

17* (16,367)

13 (13,305)

13 (12,380)

18* (17,984)

18* (17,732)

3 (2,950)

16* (16,020)

17* (16,808)

14 (13,878)

20* (20,195)

29* (29,094)

36 (35,898)

1 (555)

7* (7,331)

12 (11,666)

19* (18,358)

25* (25,137)

33* (32,679)

1 (527)

48* (19,761)

23* (9,449)

7 (3,000)

8 (3,483)

20* (8,374)

17* (6,881)

14 (5,860)

12 (5,063)

18* (7,298)

19* (7,803)

3 (1,201)

16* (6,648)

18 (7,286)

14 (5,799)

20* (8,185)

29* (12,160)

39 (16,247)

<1* (203)

7* (3,006)

11* (4,694)

18 (7,276)

24 (9,853)

36 (14,768)

<1* (192)

50* (7,342)

22 (3,255)

6* (945)

8 (1,221)

20* (3,020)

17* (2,525)

15 (2,208)

12 (1,759)

15* (2,266)

20* (3,011)

3 (487)

17* (2,503)

19 (2,765)

14 (2,028)

18* (2,628)

30* (4,378)

45* (6,638)

<1* (66)

7* (1,045)

10* (1,520)

16* (2,362)

21* (3,158)

40* (5,983)

<1* (62)

(51)

(51)

51* (5,277)

21 (2,185)

5* (565)

8 (840)

20* (2,138)

18 (1,904)

14 (1,506)

11* (1,104)

13* (1,363)

2*3 (2,425)

5* (471)

18 (1,901)

19 (1,966)

13* (1,331)

15* (1,585)

31* (3,186)

54* (5,597)

<1

6* (650)

9* (950)

12* (1,298)

18* (1,894)

47* (4,952)

<1

150

<1 (38)

Did not Occur

39* (14,895)
12* (4,505)
12* (4,745)
10* (3,745)
<1 (36)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

6* (2,414)
16* (6,360)
43* (16,804)
23* (8,928)
<1* (145)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

6* (2,456)
19* (7,280)
46* (17,845)
23* (8,872)
<1 (17)

Supervision

Limited Assistance

Extensive Assistance

Total Dependence

Did not Occur

5* (1,862)
43* (16,772)

Extensive Assistance

2 (891)

Supervision

Limited Assistance

1 (300)

Independent

Bathing

6* (2,201)

Independent

Personal Hygiene

10* (4,020)

Independent

Toilet

28* (10,745)

Independent

Eating

20* (7,737)

Total Dependence

48 (69,669)

6 (8,647)

3 (4,842)

1 (1,464)

<1 (61)

18 (26,558)

45 (65,812)

21 (31,380)

8 (11,812)

7 (10,601)

<1 (346)

18 (26,817)

41 (60,488)

18 (26,861)

8 (11,789)

14 (19,923)

<1 (90)

6 (9,476)

9 (13,087)

11 (15,577)

42 (60,794)

32 (47,200)

<1 (139)

16 (23,340)

50* (49,508)

6 (6,272)

4* (3,712)

1 (1,193)

<1 (31)

16* (15,493)

45 (44,401)

23* (22,302)

9* (8,524)

8* (8,194)

<1* (160)

16* (16,280)

41 (40,514)

19* (18,643)

8 (8,301)

15* (15,047)

<1 (55)

5* (4,610)

7* (6,816)

9* (9,170)

43* (42,416)

36* (35,878)

<1 (68)

14* (13,715)

51* (21,101)

6 (2,648)

4* (1,497)

1 (507)

<1 (19)

15* (6,188)

46* (18,943)

22 (9,133)

8 (3,460)

9* (3,536)

<1* (52)

17* (6,880)

42 (17,388)

19 (7,684)

8 (3,239)

15* (6,036)

<1* (9)

4* (1,491)

6* (2,289)

9* (3,524)

44* (18,192)

38* (15,774)

<1 (27)

13* (5,559)

51* (7,526)

6 (946)

3 (482)

1 (179)

<1 (5)

15* (2,200)

47* (7,023)

21 (3,163)

7 (1,104)

9* (1,294)

<1 (23)

18 (2,704)

43* (6,374)

17 (2,585)

7* (1,082)

14 (2,021)

<1 (4)

3* (459)

5* (668)

8* (1,196)

43* (6,394)

41* (6,068)

<1 (9)

14* (2,017)
(6)

(2)

(28)

(4)

49* (5,150)

5 (566)

3 (290)

1 (126)

<1

17* (1,725)

49* (5,091)

20* (2,045)

6* (675)

9* (900)

<1

22* (2,256)

43* (4,516)

16* (1,698)

6* (651)

12* (1,291)

<1

3* (269)

4* (393)

7* (735)

42 (4,341)

45* (4,700)

<1

15 (1,567)

151

4 (1,719)

44* (17,127)
4 (6,331)

38 (55,271)
4 (4,007)

35* (34,253)

Note: * Significantly different from the reference group (normal BMI) p<0.05.

Did not Occur

Total Dependence
4 (1,666)

34* (13,860)
4 (588)

34* (5,068)
4 (417)

37 (3,891)

152

Bed Mobility
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Transfer
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Walk in Room
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Walk in Corridor
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Locomotion on Unit
No help

Activity of Daily Living (ADL)
Support Provided

(N=350,348), 2010-2020

(68,390)
(36,189)
(126,929)
(116,654)
(2,186)
(85,932)
(46,489)
(76,343)
(15,043)
(126,541)
(77,181)
(45,664)
(73,002)
(15,155)
(139,346)
(86,353)

20
10
36
33
1
25
13
22
4
36
22
13
21
4
40
25

<1

(91,750)
(36,597)
(124,427)
(97,396)
(178)

26
10
36
28

Total
(100%, N=350,348)
%
(n)

Total

24

22^
13
21^
4
39

25^
13
22^
4
36

20^
10
37^
33
1

26^
11^
36^
27
<1

(69,298)

(63,225)
(36,932)
(60,487)
(12,332)
(110,864)

(70,337)
(37,487)
(63,035)
(12,143)
(100,838)

(56,118)
(29,278)
(104,055)
(92,566)
(1,823)

(75,209)
(29,838)
(102,151)
(76,515)
(127)

<30 kg/m2
(81%, n=283,840)
%
(n)

26^

21
13
19
4
43^

23
14^
20
4
39^

18
10
34
36^
1

25
10
33
31^
<1

(17,055)

(13,956)
(8,732)
(12,515)
(2,823)
(28,482)

(15,595)
(9,002)
(13,308)
(2,900)
(25,703)

(12,272)
(6,911)
(22,874)
(24,088)
(363)

(16,541)
(6,759)
(22,276)
(20,881)
(51)

≥ 30 kg/m2
(19%, n=66,508)
%
(n)

<or ≥ 30 kg/m2

Activities of Daily Living (ADLs) Assistance Provided to Persons Newly Residing in a Long-term Care Facility by Obesity Status

Appendix 5

153

Set-up help only
One person assist
Two + persons assist
Did not occur
Locomotion off Unit
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Dressing
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Eating
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Toilet
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Personal Hygiene
No help
Set-up help only
One person assist
Two + persons assist
Did not occur
Bathing
No help
Set-up help only

(54,972)
(189,118)
(7,764)
(12,141)
(53,343)
(39,998)
(173,111)
(5,325)
(78,571)
(19,337)
(25,573)
(240,063)
(65,088)
(287)
(49,558)
(202,103)
(97,152)
(1,339)
(196)
(38,978)
(25,524)
(170,215)
(114,877)
(754)
(17,032)
(29,264)
(237,526)
(66,389)
(137)
(2,731)
(11,931)

16
54
2
3
15
11
49
2
22
6
7
69
19
0
14
58
28
0
0
11
7
49
33
0
5
8
68
19
0
1
3

1
3

5
8
68^
18
<1

11
7
49^
32
<1^

14
57
29^
<1^
<1^

5
7
69^
18
<1

15
11
50^
1
23^

15
55^
2
4^

(2,149)
(9,538)

(13,537)
(23,545)
(194,377)
(52,272)
(109)

(31,665)
(20,755)
(139,776)
(90,993)
(651)

(38,512)
(160,659)
(83,373)
(1,115)
(181)

(15,550)
(20,819)
(196,014)
(51,212)
(245)

(42,016)
(31,531)
(141,120)
(4,134)
(65,039)

(43,644)
(154,806)
(6,110)
(9,982)

1
4^

5^
9^
65
21^*
<1

11
7
46
36^
<1

17^
62^
21
<1
<1

6^
7
66
21^
<1

17^
13^
48
2^
20

17^
52
2^
3

(582)
(2,393)

(3,495)
(5,719)
(43,149)
(14,117)
(28)

(7,313)
(4,769)
(30,439)
(23,884)
(103)

(11,046)
(41,444)
(13,779)
(224)
(15)

(3,787)
(4,754)
(44,049)
(13,876)
(42)

(11,327)
(8,467)
(31,991)
(1,191)
(13,532)

(11,328)
(34,312)
(1,654)
(2,159)

154

61
30
4

(215,119)
(105,838)
(14,728)
62^
30
4

(175,975)
(84,121)
(12,057)

59
33^
4

(39,144)
(21,717)
(2,671)

24.9 kg/m2).

Note. a) ^ Significantly larger when comparing obese and non-obese groups (p<0.05) . b) * Significantly different from the reference group (normal BMI, 18.5-

One person assist
Two + persons assist
Did not occur

155

9*
39*
30*
<1

Set-up help only

One person assist

Two + persons assist

Did not occur

8*
39*
37*
1*

Set-up help only

One person assist

Two + persons assist

Did not occur
18*
11*
23

No help

Set-up help only

One person assist

Walk in Room

14*

No help

Transfer

22*

(8,913)

(4,160)

(7,121)

(503)

(14,368)

(15,008)

(3,282)

(5,510)

(27)

(11,717)

(15,044)

(3,520)

(8,363)

22

13

25

1

32

37

10

20

<1

27

6

10

27

(32,825)

(19,268)

(36,434)

(837)

(47,237)

(54,006)

(14,926)

(29,218)

(55)

(38,775)

(53,034)

(15,319)

(39,041)

(n)

%

%

(n)

Normal
(42%, n=146,224)

Underweight
(11%, n=38,671)

No help

Bed Mobility

Activity of Daily
Living (ADL)
Support Provided

(N=350,348), 2010-2020

22*

14*

27*

<1

31*

35*

11*

22*

<1

26

34*

11

28*

%

(21,297)

(14,059)

(26,782)

(483)

(30,961)

(35,041)

(11,070)

(21,390)

(45)

(26,023)

(34,073)

(10,999)

(27,805)

(n)

Overweight
(28%, n=98,945)

21*

14*

25

<1

34*

35*

11*

20

<1

29*

34*

11

26

%

(8,548)

(5,781)

(10,403)

(190)

(14,005)

(14,425)

(4,473)

(8,186)

(19)

(11,940)

(14,128)

(4,373)

(10,819)

(n)

Class I
(12%, n=41,279)

Body Mass Index (BMI) Categories

20*

13

22*

1

38*

34*

10

17*

<1

33*

34*

10

24*

%

(2,903)

(1,981)

(3,261)

(80)

(5,577)

(5,096)

(1,488)

(2,548)

(11)

(4,824)

(4,973)

(1,476)

(3,505)

(n)

Class II
(4%, n=14,789)

18*

12*

18*

1*

43*

32*

9*

15*

<1

39*

30*

9*

21*

%

(1,857)

(1,240)

(1,931

(93)

(4,506)

(3,353)

(950)

(1,538)

(21)

(4,117)

(3,175)

(910)

(2,217)

(n)

Class III
(3%, n=10,440)

Activities of Daily Living (ADLs) Assistance Provided to Persons Newly Residing in a Long-term Care Facility by Body Mass Index

Appendix 6

156

21
4

One person assist

Two + persons assist

4*
6*
71*
19*
<1

No help

Set-up help only

One person assist

Two + persons assist

Did not occur

Dressing

26

Did not occur

53*

One person assist
1

8*

Set-up help only

Two + persons assist

11*

No help

Locomotion off Unit

5*

Did not occur

62*

One person assist
2

12*

Set-up help only

Two + persons assist

18*

No help

Locomotion on Unit

48*

10*

Set-up help only

Did not occur

16*

43*

4

No help

Walk in Corridor

Did not occur

Two + persons assist

(38)

(7,496)

(27,304)

(2,272)

(1,561)

(10,158)

(574)

(20,582)

(3,212)

(4,145)

(2,048)

(897)

(24,110)

(4,695)

(6,921)

(18,550)

(1,702)

(8,229)

(3,943)

(6,247)

(16,762)

(1,715)

<1

18

69

7

5

23

1

50

11

15

3

2

55

15

24

39

4

22

13

22

35

4

(139)

(26,117)

(101,259)

(10,784)

(7,925)

(33,704)

(2,094)

(72,823)

(16,178)

(21,425)

(4,984)

(3,057)

(80,151)

(22,361)

(35,671)

(56,416)

(6,449)

(31,596)

(19,021)

(32,742)

(51,397)

(6,300)

<1

18

68*

8*

6*

21

1

48*

12*

17*

3*

2

51*

17*

27*

36*

4

21*

14*

24*

33*

4

(68)

(17,599)

(67,451)

(7,763)

(6,064)

(21,177)

(1,466)

(47,715)

(12,141)

(16,446)

(2,950)

(2,156)

(50,545)

(16,588)

(26,706)

(35,898)

(4,181)

(20,662)

(13,968)

(24,236)

(32,679)

(4,128

<1

19*

67*

8

6*

20

2

48*

13*

17*

3*

2

51*

17*

26*

39

4

20*

14*

23

36

4

(27)

(7,996)

(27,743)

(3,120)

(2,393)

(8,374)

(656)

(19,986)

(5,336)

(6,927)

(1,201)

(924)

(21,235)

(7,097)

(10,822)

(16,247)

(1,757)

(8,211)

(5,717)

(9,347)

(14,768)

(1,779)

<1

21*

66*

7

6

20

2*

48*

12*

17*

3

3*

52*

17*

25

45*

4

18*

13

20*

40*

4

(9)

(3,130)

(9,786)

(1,027)

(837)

(3,020)

(278)

(7,136)

(1,848)

(2,507)

(487)

(383)

(7,685)

(2,496)

(3,738)

(6,638)

(635)

(2,702)

(1,880)

(2,934)

(5,983)

(661)

<1

26*

62*

6*

5

20

2*

47*

12*

18*

5*

3*

52*

17*

24

54*

4

15*

11*

16*

47*

4

(6)

(2,750)

(6,520)

(607)

(557)

(2,138)

(257)

(4,869)

(1,283)

(1,893)

(471)

(347)

(5,392)

(1,735)

(2,495)

(5,597)

(431)

(1,602)

(1,135)

(1,675)

(4,952)

(460)

157

51*
38*
<1
<1

Set-up help only

One person assist

Two + persons assist

Did not occur

6*
50
35
<1

Set-up help only

One person assist

Two + persons assist

Did not occur

7*
70*
20*
<1

Set-up help only

One person assist

Two + persons assist

Did not occur

61
31*

One person assist

Two + persons assist
4

2*

Set-up help only

Did not occur

1

No help

Bathing

4

No help

Personal Hygiene

9*

No help

Toilet

11*

No help

Eating

(1,719)

(12,077)

(23,733)

(930)

(212)

(17)

(7,578)

(27,071)

(2,575)

(1,430)

(145)

(13,650)

(19,369)

(2,214)

(3,293)

(36)

(181)

(14,531)

(19,796)

(4,127)

4

29

62

3

1

<1

18

69

8

5

<1

32

49

7

11

<1

<1

30

56

13

(6,331)

(42,997)

(90,912)

(4,895)

(1,089)

(61)

(26,730)

(100,472)

(12,177)

(6,784)

(346)

(46,491)

(72,363)

(10,835)

(16,189)

(90)

(571)

(44,044)

(82,178)

(19,341)

4

29

62

4*

1

<1

18

68*

9*

5*

<1

31*

49*

8*

12*

<1

<1

25*

59*

15*

(4,007)

(29,047)

(61,330)

(3,713)

(848)

(31)

(17,964)

(66,834)

(8,793)

(5,323)

(160)

(30,852)

(48,044)

(7,706)

(12,183)

(55)

(363)

(24,798)

(58,685)

(15,044)

4

31*

60*

4*

1

<1

20*

66*

9*

5*

<1

34*

47*

7

12

<1

<1

22*

62*

16*

(1,666)

(12,853)

(24,839)

(1,548)

(373)

(19)

(8,105)

(27,275)

(3,676)

(2,204)

(52)

(14,030)

(19,337)

(3,080)

(4,780)

(9)

(136)

(9,116)

(25,389)

(6,629)

4

33*

58*

4

1

<1

22*

65*

8

5*

<1

37*

45*

7

11

<1

<1

20*

63*

17*

(588)

(4,928)

(8,604)

(543)

(126)

(5)

(3,211)

(9,545)

(1,231)

(797)

(23)

(5,422)

(6,724)

(1,051)

(1,569)

(4)

(46)

(2,901)

(9,324)

(2,514)

4

38*

55*

3

1

<1

27*

61*

8

5

<1

42*

42*

6*

9*

<1

<1

17*

64*

18*

(417)

(3,937)

(5,701)

(302)

(83)

(4)

(2,801)

(6,329)

(812)

(494)

(28)

(4,432)

(4,378)

(638)

(964)

(2)

(42)

(1,762)

(6,731)

(1,903)

158

2010

3
10
19
24
20
23

(n=5,630)

3
10
21
25
20
21

(n=24,184
)

2012
3
11
21
25
20
20

(n=24,817)

2013
3
11
20
25
20
20

(n=26,564
)

2014
3
11
21
25
20
20

(n=28,227)

Year
2015
2016
3
11
21
24
20
20

(n=26,952
)

3
12
20
25
20
19

(n=27,226)

2017

2018
3
12
21
23
20
19

(n=27,768
)

3
12
21
24
19
19

(n=26,790)

2019

3
8
17
25
23
23

(n=5,642)

3
8
17
24
22
25

(n=5,397)

3
9
18
26
20
25

(n=5,541)

3
9
19
25
21
23

(n=5,963)

3
10
18
25
21
24

(n=6,731)

3
9
19
24
21
24

(n=6,678)

3
9
18
23
22
25

(n=6,870)

3
9
19
23
21
24

(n=6,975)

3
10
19
24
21
23

(n=6,731)

Persons newly residing in s LTCF with obesity with the number of conditions (%)
Year
2011
2012
2013
2014
2015
2016
2017
2018
2019

3
10
21
25
20
20

(n=25,840)

(n=25,947
)

3
11
21
25
20
19

2011

2010

Persons newly residing in s LTCF without obesity with the number of conditions (%)

3
9
18
25
21
25

(n=4,350)

2020

3
11
21
25
20
20

(n=19,525)

2020

Asthma, Liver Disease, Hip Fracture.

(a combination of Arteriosclerotic heart disease (ASHD), Congestive Heart Failure, and 'Other Cardiovascular disease'), Emphysema/COPD, Anemia, Cancer,

Note: a) Conditions considered: Hypertension, Dementia/Alzheimer's (combined), Arthritis, Diabetes Mellitus, Osteoporosis, Depression, Stroke, Heart disease

0 Conditions
1
2
3
4
5+

0 Conditions
1
2
3
4
5+

Number of
Conditions

Annual Rates of Multi-Morbidities Amongst Persons Newly Residing in a Long-term Care Facility (N=350,348), 2010-2020

Appendix 7

159

Normal

22* (4,657)
19* (3,923)
10* (2.057)

Walking In Room

Walking In Corridor

Toileting
1 (132)

10* (2,120)

Locomotion off Unit

Bathing

19* (4,064)

Locomotion on Unit

4* (880)

18* (3,756)

Transfer

Personal hygiene

26* (5.435)

5* (994)

Dressing

Bed Mobility

24* (5,029)

% (n)

1 (752)

6 (4,897)

14 (11,561)

26 (22,363)

31 (26,648)

14 (11,654)

26 (22,511)

26 (22,170)

34 (28,761)

7 (5,773)

29 (24,842)

% (n)

11%, n=20,976 45%, n=85,139

Underweight

Eating

Independent Self-Performance

Activity of Daily Living

1 (562)

6 (3,457)

15* (8,330)

30* (16,462)

35* (19,481)

16* (8,635)

30* (16,405)

29* (16,029)

37* (20,175)

7 (4,106)

33* (18,158)

% (n)

29%,
n=55,233

Overweight

Class II

Class III

1 (214)

6 (1,247)

15* (2,997)

29* (5,932)

35* (7,053)

16* (3,200)

29* (5,943)

28* (5,657)

35 (7,181)

7 (1,452)

34* (6,956)

% (n)

1 (67)

6 (353)

14 (792)

28 (1,601)

33 (1,913)

16* (936)

28 (1,646)

26 (1,497)

32 (1,888)

7 (387)

35* (2,042)

% (n)

1 (21)

6 (164)

13 (364)

29 (730)

31 (871)

18* (501)

29 (826)

24 (671)

31 (888)

7 (199)

38* (1,083)

% (n)

11%, n=20,389 3%, n=5,827 1%, n=2,851

Class I

With Dementia/ Alzheimer's (54%, n=190,415)
Body Mass Index (BMI) Categories

for Persons Newly Residing in a LTCFs (N=350,348), 2010-2020

Independent Self Performance of Activities of Daily Living (ADLs) Stratified by Dementia/ Alzheimer's and Body Mass Index (BMI)

Appendix 8

160

26* (4,597)
15* (2,714)
20* (3,575)
14* (2.414)
18* (3.228)
15* (2,596)
11* (1,963)
7* (1,321)

Bed Mobility

Transfer

Locomotion on Unit

Locomotion off Unit

Walking In Room

Walking In Corridor

Toileting

Personal hygiene
1 (712)

9 (5,704)

14 (8,362)

18 (11,292)

22 (13.590)

18 (11.033)

26 (15,892)

19 (11,358)

29 (17,950)

9 (5,476)

37 (22,358)

% (n)

1 (631)

11* (4,737)

15* (6,717)

20* (8,675)

24* (10.291)

21* (9.097)

29* (12,689)

20* (8,796)

30 (13,302)

10* (4,431)

41* (17,720)

% (n)

27%,
n=43,712

Overweight

Class II

Class III

1 (293)

11* (2,289)

15 (3,039)

19* (3,921)

23* (4.721)

22* (4.603)

30* (6,217)

19 (4,006)

29 (5,989)

10 (2,031)

42* (8,818)

% (n)

1 (112)

10 (941)

14 (1,229)

17 (1,557)

21 (1,864)

23* (2.075)

30* (2,732)

18 (1,593)

27* (2,434)

9 (834)

45* (4,026)

% (n)

1 (206)

10 (736)

12 (927)

15* (1,164)

19* (1,432)

25* (1,924)

31* (2,360)

16* (1,215)

25* (1,864)

8 (641)

48* (3,617)

% (n)

13%, n=20,890 6%, n=8,962 5%, n=7,589

Class I

Class I, II = Class II, III = Class II.

Note. a) * Significantly different from the reference group (normal BMI) of the stratified group (p ≤0.001) b) U=Underweight, N=Normal, O=Overweight, I =

1 (168)

7* (1,258)

Dressing

% (n)
32* (5,716)

Bathing

Normal

11%, n=17,695 38%, n=61,085

Underweight

Eating

Independent Self-Performance

Activity of Daily Living

Without Dementia/ Alzheimer's (46%, n=159,933)

161